‘I don’t ramble’: Trump sinks to new levels of delusion
The presidet bounced between topics ranging from renaming oceans to insisting he doesn’t ramble—while rambling.
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London’s most spectacular private dining rooms
London has no shortage of private dining rooms, ranging from discreet enclaves and stylish nooks to cordoned-off, clandestine…
#London #Britain #UnitedKingdom #UK #GB #England #Headlines #News #Europe #EU #EatandDrink #dining #Londondining
https://www.europesays.com/gbr/london/42980/ -
Non-destructive read-write badblocks test made it ~32 GB into the drive before falling over (on a read, rather than a write, surprisingly). After restarting, a subsequent test starting from a few blocks prior and ranging through to a few blocks after runs just fine, so it really does seem like a flaky drive rather than a couple of bad sectors throwing the controller for a loop.
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The AYN Ordin 3 Portal handheld game console with a 7 inch, 120 Hz OLED display and Qualcomm Dragonwing Q8 chip is now available for $399 and up, with RAM/Storage options ranging from 12GB+128GB to 16GB+1TB. https://www.ayntec.com/products/odin3-portal?variant=50552313184448 #AYN_Odin_3_Portal #HandheldGameConsole
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Microsoft, partners disrupt phishing kit ecosystem behind cybercrime operations
Microsoft and its partners dismantle three parts of a wide-ranging cybercrime marketplace: YAM Store, CoGUI, and Iron Man
https://justpaste.in/news/microsoft-partners-disrupt-phishing-kit-ecosystem-cybercrime-operations/
#cybercrime #cybersecurity #Microsoft #onlinescams #phishing
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‘Us eleven versus 90,000!’ – Jordan Pickford reveals greatest England games after World Cup drama
England goalkeeper Jordan Pickford revisited five of his most iconic international appearances, ranging from debut nerves to high-stakes…
#Football #Soccer #WorldCup2026 #England #J.Pickford
https://www.europesays.com/football/76555/ -
Nürnberg | laufende Entschärfung | Radio 8
Die Entschärfung läuft. In der Trierer Straße in Nürnberg, südöstlich des Südfriedhofs und in der Nähe des Rangierbahnhofs,…
#Nuernberg #Nuremberg #Deutschland #Deutsch #DE #Schlagzeilen #Headlines #Nachrichten #News #Europe #Europa #EU #Nürnberg #Bayern #Germany
https://www.europesays.com/de/1360181/ -
https://www.europesays.com/it/741742/ Como-Manchester United: da Florence Pugh a Tom Welling, tutti i vip in tribuna #amico #blinders #campo #carrick #Celebrità #Celebrities #champions #cole #Como #Entertainment #finn #FinnCole #Florence #FlorencePugh #giggs #Intrattenimento #IT #Italia #Italy #joe #JoeFinn #JoeFinnCole #oscar #peaky #PeakyBlinders #pugh #ryan #RyanGiggs #serata #sinigaglia #stelle #superman #tribuna #united
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New hotels: Oaks Vacation Club Kyoto Gojo, Jakarta Marriott Hotel Gelora and more
Oaks Vacation Club Kyoto Gojo Oaks Vacation Club Kyoto Gojo, JapanLocated one block from Nishiki Market in central Kyoto, Oaks Vacation Club Kyoto Gojo features 20 rooms ranging from 20m² to 42m², from Standard Double Rooms to a Japanese Suite. Shijo Station…
#Japan #JP #Kyoto #kyotonews #news #京都 #京都府
https://www.alojapan.com/1556744/new-hotels-oaks-vacation-club-kyoto-gojo-jakarta-marriott-hotel-gelora-and-more/ -
(4/4)
So, in that sense, Dan J is not doing anything out of character for an AIP'er. Acting as a spoiler for the orthodox GOP has been the AIP's role as long as I've known them! I think a few Democratic governors can thank AIP candidates for their wins, but that's absolutely on the fringies, not the Ds!*Today's articles suggest that Alaska's fairly recent adoption of ranked-choice voting** is what's changed, but they are undervaluing the other big change: MAGA.
There's no need for a right flank party in Alaska since MAGA captured the GOP. What I think is funny here is that Dan J's big sin isn't that he isn't RW enough, it's that Dan S is Trump loyal!
Help yourself to looking into some of the characters in the AIP history--ranging from colorful to terrifying.
(/end)
*please take note of this lesson on the consequences of purity tests.
**I'm not a fan.
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Armory – Echoes of the Astrolith Review By KenstrositySci-fi and speed metal. If that isn’t enough to get your hyperdrives boosted, then I don’t know what will. This particular combo isn’t as well represented in the metalverse as some of the more common varieties—sci-fi and black metal, campy horror and death metal, you know the ones—which puts Swedish speed freaks Armory in a prime position to dominate. With three full lengths under their belt so far, one of which positively received by our own Ape ov Steel, and a new vocalist at the helm, what new wonders await in fourth excursion Echoes of the Astrolith?
Well, MOAR speed, of course! This is high-octane, laser-focused fare set to collide with Earth at warp 9.5. Touchstones ranging from Agent Steel to Bütcher to Riot City inform Armory’s various traipses through speedy riffs, heavy metal bravado, and black metal flourishes. Melodies move with an almost Xoth-like wiggliness that brings a lot of whimsy and exuberance to otherwise dark and seedy songwriting (“Interceptor Squadron,” “Frequencies of Terror”). Riffs pound and pummel with the vigor of death metal without venturing into the structures that genre often builds, which gives Armory a sense of heft and fullness not unlike what Dark Angel’s seminal Darkness Descends must’ve felt like when it was new (“Sanity Disposed,” “The Final Invention,” “Astrolith (Rising)”). Of course, it wouldn’t be speed metal without 10,000^10 ft/lbs of torque to send it flying off the galactic rails, and thankfully Armory fueled up extra before launching. Echoes of the Astrolith moves with an urgency rarified even in this vigorous style (“Return of the True Godz,” “Frequencies of Terror,” “Pillars of Fire”).
While new vocalist Chris Rostoff acquits himself with aplomb here, guitarists G.Sundin and N.Ingelman steal the show and make Echoes of the Astrolith a clinic in guitar wizardry. If it isn’t by way of screaming solos that nosedive and pitch back up in aerobatic fashion (“Interceptor Squadron,” “Frequencies of Terror”), Armory’s axe arsenal displays electrified pyrotechnics through monolithic riffs that find a perfect center position between death, thrash, and speed (“Astrolith (Rising)”); or with melodious leads and tremolo flares that writhe impatiently from measure to measure as they pull the rest of the band into unexplored space (“Return of the True Godz,” “Cosmic Dreams,” “Pillars of Fire”). A.Holmström blisters his way through asteroid fields with double-bass pummels, sharp blasts, and menacing gallops all throughout. Yet, his unhinged fill work sends his weaponry into overdrive at every opportunity to leave even the space dust in Armory’s wake obliterated (“Interceptor Squadron,” “Omens,” “Sanity Disposed”). Chris Rostoff, as previously mentioned, proves himself an absolute powerhouse on the mic here. His sneering bark and soaring wails are a perfect fit for this sound, and his scalpel-precise pitch-work is nothing short of astounding at the record’s peaks (“Interceptor Squadron,” “Pillars of Fire”). I just wish I could hear Jesper Lundin’s bass better. I’m sure he’s keeping up with the band with ease, but his presence lacks oomph in many quadrants and what playing I do hear with clarity follows the path laid by the rest of the rhythm section (“Frequencies of Terror”).
Quality speed metal albums like this make me rethink my high estimation of other quality acts like Hellripper ever so slightly, but it’s hard to know what kind of staying power Echoes of the Astrolith has. Certain highlights such as “Interceptor Squadron” are sure to be trapped in the event horizon that is my playlist rotation. At 39 minutes, Echoes as a whole is tight enough to get regular spins out of me regardless of long-term memorability. However, a small question of consistency in songwriting quality nags at my thoughts. “Cosmic Dreams” is fun, but its mid-paced and slightly repetitive riffing introduces a poorly timed speed bump in the first quarter. In the second half, fluffy three-minute instrumental interlude “Spaceworkz” once again interrupts Echoes of the Astrolith’s momentum right before two high-octane bangers save the final third from certain doom. In the center, Echoes of the Astrolith keeps up a consistent level of songwriting quality—one that any band in this space should be proud to have penned—but a preponderance of overlong intros (“Omens”), and overlong outros (“The Final Invention”) conspire to pull these works back from greatness.
You know speed metal is really fucking good if I’m close to calling it Great, and Echoes of the Astrolith is almost great. Armory deliver an impressive salvo of cooler-than-you’ll-ever-be speed metal tracks embellished with blackened, deathened, and thrashened elements the likes of which are sure to set your blasters to kill. If you’re looking for something to jam while you scream directly into a space-bound dogfight with the enemy mothership, look no further than Echoes of the Astrolith!
Rating: Very Good
#2026 #35 #AgentSteel #Armory #BlackenedSpeedMetal #Bütcher #DarkAngel #DyingVictimsProductions #EchoesOfTheAstrolith #Hellripper #Oct26 #Review #Reviews #RiotCity #SpeedMetal #SpeedThrash #SwedishMetal #Xoth
DR: 10 | Format Reviewed: 320 kb/s mp3
Label: Dying Victims Productions
Websites: Bandcamp | Official
Releases Worldwide: October 23rd, 2026 -
DATE: October 24, 2026 at 06:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: People with psychosis and a history of aggression are more likely to mistake negative emotions for positive ones
A study in Sweden found that people with psychotic spectrum disorders had more difficulty recognizing emotions in others than healthy people, and that those who also had a history of interpersonal aggression had the most difficulty of all. People in the aggression group were also more likely to mistake negative emotions for positive ones. The paper was published in Schizophrenia.
Recognizing emotions in other people is essential for successful social interaction because facial expressions, tone of voice, and body movements provide important clues about how others feel. When these signals are misunderstood, communication can break down and inappropriate social responses may become more likely.
Difficulties with emotion recognition are common in psychotic spectrum disorders, which in this study included schizophrenia, schizoaffective disorder, delusional disorder, and bipolar disorder with psychotic features. Research has shown that people with these disorders tend to have trouble identifying emotions from faces, voices, and body movements, even when these expressions are presented dynamically rather than as static images. These difficulties appear to be especially pronounced for negative emotions, but are present with positive emotions as well.
People with schizophrenia, for example, often confuse one negative emotion with another or interpret neutral expressions as negative. Such errors may reflect broader problems in perception, memory, language, and other cognitive processes involved in understanding emotional information. Researchers have also investigated whether impaired emotion recognition is related to interpersonal aggression in people with psychotic disorders, but the findings have been mixed.
Study author Gabriela Gavalova of Karolinska Institutet and colleagues investigated how well people with psychotic spectrum disorders recognize a wide range of emotions conveyed dynamically through facial, vocal, and bodily expressions. They compared three groups: people with psychotic spectrum disorders and a history of interpersonal aggression, people with these disorders but no history of interpersonal aggression, and healthy individuals.
They hypothesized that misclassification of emotions would be greatest in people with psychotic spectrum disorders and a history of interpersonal aggression, intermediate in people with these disorders but no history of aggression, and lowest in healthy individuals.
The study included 79 people with psychotic spectrum disorders and a history of interpersonal aggression, recruited from Forensic Psychiatry Stockholm; 72 people with these disorders but no history of interpersonal aggression, recruited at psychiatric outpatient clinics in Stockholm; and 86 healthy individuals recruited through Sweden’s State Person Address Registry. The groups were matched by age and gender, with men making up between 69% and 75% of each group and average ages ranging from 35 to 39 years. Participants with psychotic disorders had been clinically stable, with no changes in medication, for at least three months before testing.
Most participants with psychotic spectrum disorders had schizophrenia (79% in the aggression group and 86% in the non-aggression group). Information about the type and number of aggressive acts was obtained from crime reports, forensic psychiatric assessments, hospital case records, and participants’ self-reports. Acts of interpersonal aggression were defined as threats to life, assault, grievous bodily harm, or murder or manslaughter; about half of the participants in the aggression group had committed assault, and about a third had been convicted of grievous bodily harm.
The groups also differed in other ways. More than three-quarters of the aggression group had a history of alcohol or substance abuse, compared with a third of the non-aggression group and 7% of healthy participants, and more than half of the aggression group had not completed education beyond primary school, compared with 15% of the non-aggression group. The aggression group also scored lower on a test of fluid intelligence than the non-aggression group.
Participants completed psychiatric screening, a test of fluid intelligence (the Matrix Reasoning subtest of the Wechsler Adult Intelligence Scale-IV), and a test of psychomotor speed. To assess how well they knew the words used to name emotions, they picked synonyms for 14 emotion words. They then completed the Emotion Recognition Assessment in Multiple modalities test, in which they watched and listened to short clips of actors expressing 12 different emotions through their faces, voices, and bodies while speaking nonsense sentences. Clips were presented as video only, audio only, or video with sound, and participants chose the emotion being expressed from a list of all 12.
As expected, people with psychotic spectrum disorders and a history of interpersonal aggression performed the worst. Depending on the emotion, their accuracy ranged from 25% for despair to 54% for anger. Participants with psychotic spectrum disorders but no history of aggression performed somewhat better, with accuracies ranging from 29% for despair to 66% for anger, and healthy participants performed the best, with accuracies ranging from 39% to 68%.
All three groups performed well above chance, and the gaps between the groups were similar across emotions and across video, audio, and combined presentations. The authors suggest this points to general cognitive and perceptual difficulties rather than problems specific to particular emotions or senses. Across groups, emotions were recognized best when presented with both video and sound.
The most distinctive finding involved the kinds of errors people made. Participants in the aggression group misread negative emotions as positive ones in 14% of cases, about 1.2 times as often as the non-aggression group and twice as often as healthy participants. The authors speculate that such errors could lead people to miss signs that their behavior is upsetting others, removing a social cue that might otherwise stop an escalating interaction.
Among participants with psychotic disorders, the strongest predictors of emotion recognition were fluid intelligence and understanding of emotion words, followed by gender, with women outperforming men, and educational attainment. Unexpectedly, a history of substance abuse was linked to better performance once other factors were accounted for, a result the authors say may be a statistical artifact and should be interpreted with caution. A history of aggression still predicted poorer emotion recognition after these factors were taken into account, although it explained only about 2% of the additional variation in performance.
“In summary, individuals with PSD [psychotic spectrum disorder] and a history of interpersonal aggression exhibit more pronounced deficits in emotion recognition than those with PSD alone. This underscores the potential value of incorporating emotion recognition assessment and training into clinical interventions to reduce aggression risk and improve social functioning in individuals with PSD,” the study authors concluded.
The study contributes to the scientific understanding of the links between emotion recognition abilities and mental health. However, it should be noted that the design of the study does not allow any causal inferences to be derived from the results. The groups also differed in education, intelligence, and substance use history, and other unmeasured differences between them cannot be ruled out.
Participants were tested while clinically stable, so the study could not capture emotion recognition during acute psychosis or agitation. The emotions were portrayed by actors rather than expressed spontaneously, and the clips, which were developed in Switzerland and featured white European actors, may have been interpreted differently by participants from other backgrounds.
The paper, “Emotion recognition misclassification patterns in individuals with psychotic spectrum disorders and history of interpersonal aggression,” was authored by Gabriela Gavalova, Petri Laukka, Lennart Högman, Malin V. Källman, Marianne Kristiansson, Märta Wallinius, Håkan Fischer, and Anette G. M. Johansson.
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #MentalHealth #Psychosis #Schizophrenia #Psychology #EmotionRecognition #EmotionalIntelligence #MentalHealthResearch #SocialCognition #AggressionResearch #Psychiatry
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Governance Attack Surface Review: Spark Liquidity Layer
Target Protocol: Spark Liquidity Layer (TVL: $2739.3M)Spark Liquidity Layer – Governance Attack‑Surface Review
Date: 24 Oct 2026Prepared by: [Your Name], Senior DeFi Security Researcher & Smart‑Contract Auditor
Scope: Technical review of the on‑chain governance architecture (including tokenomics, voting, timelock, upgradeability, and cross‑chain interaction) of the Spark Liquidity Layer (SLL) – a high‑value liquidity‑routing protocol with ≈ $2.74 B TVL across Ethereum L1 and multiple L2 roll‑ups.
1. Executive Summary
The Spark Liquidity Layer (SLL) is a permissionless, composable liquidity‑aggregation protocol that relies on a token‑governed DAO to manage fee parameters, pool incentives, contract upgrades, and cross‑chain bridge configurations. The DAO’s power is concentrated in the SPARK governance token (≈ 150 M supply) and a 2‑step timelock (48 h delay) that executes approved proposals via an Upgradeable Proxy pattern.Our attack‑surface review focused on the governance stack (token, voting, proposal lifecycle, timelock, upgradeability, and cross‑chain messaging) and its interaction with the core liquidity contracts. The analysis identified nine distinct attack vectors, ranging from low‑complexity voting‑power accumulation to high‑impact upgrade‑proxy hijacking.
Overall, the governance system presents a moderate‑to‑high risk profile: Risk Score = 7 / 10. The most critical issues stem from insufficient quorum enforcement, unrestricted delegate call execution, and cross‑chain bridge governance coupling. Mitigations exist but require immediate implementation and rigorous testing.
2. Identified Attack Vectors
#VectorDescriptionPotential ImpactLikelihood*Current Mitigations1Concentrated Token Ownership & Delegation Loophole> 30 % of SPARK supply is held by a single entity (the “Founders’ Vault”). Delegation contracts allow unlimited delegation without a cap on voting power per address.Ability to push any proposal through with < 20 % quorum, potentially upgrading contracts or draining fees.High (ownership is public)Timelock delay, but no secondary safeguard.2Insufficient Quorum & Early‑Execution VulnerabilityQuorum is set at 15 % of total supply, and proposals become executable after 48 h regardless of whether the quorum is still met.An attacker can front‑run a proposal, meet quorum, then sell delegated tokens before execution, leaving the proposal still executable.Medium‑HighTimelock only; no “snapshot‑at‑execution” check.3Unrestrictedexecute(address,bytes)on TimelockThe timelock’sexecutefunction permits arbitrary target contracts and calldata, including calls todelegatecall.Malicious upgrade of core contracts, arbitrary token minting, or re‑entrancy into liquidity pools.MediumOnly timelock delay; no role‑based restriction on target contracts.4Upgradeable Proxy Admin OwnershipProxy admin is a single‑key EOA (the “Governor”) that can callupgradeToAndCall. No multi‑sig or DAO‑controlled admin.Direct upgrade to malicious implementation, bypassing DAO voting entirely.High (single point of failure)None – admin is hard‑coded.5Cross‑Chain Bridge Governance CouplingBridge parameters (e.g., L2 fee caps) are governed by the same DAO. Bridge contracts accept governance‑signed messages from L1 without additional verification.An attacker who compromises L1 governance can lock or release assets on L2, causing massive liquidity loss.MediumTimelock delay, but no L2‑specific safety checks.6Flash‑Loan‑Based Vote‑BuyingNo anti‑flash‑loan guard on token balance snapshots. An attacker can borrow a large amount of SPARK, delegate, vote, and return the loan before the proposal execution.Temporary quorum attainment for malicious proposals.MediumNone.7Proposal Spam & Gas‑DoSProposal creation cost is limited to a flat 0.5 % of TVL in fees, which is low relative to TVL. Attackers can flood the DAO with low‑value proposals, clogging the queue and raising gas costs for honest participants.Governance paralysis, increased transaction costs, potential for “censorship” attacks.MediumFee schedule; no rate‑limiting.8Insufficient Event Logging for Critical State ChangesCertain state changes (e.g., fee parameter updates) are emitted only via internal events that are not indexed by major explorers.Difficulty in on‑chain monitoring, delayed detection of malicious upgrades.LowNone.9Re‑entrancy viaonERC1155ReceivedHooks in Liquidity PoolsLiquidity pools accept ERC‑1155 tokens (representing LP shares) and call external contracts on receipt. No re‑entrancy guard on the pool’sdeposit/withdrawfunctions.An attacker could craft a malicious ERC‑1155 that re‑enters the pool during a governance‑triggered fee redistribution, siphoning funds.Low‑MediumUses OpenZeppelin’sReentrancyGuardon most functions, but not on ERC‑1155 hooks.
*Likelihood is assessed qualitatively based on public data, code review, and known attack precedents.
3. Prioritized Technical Recommendations
PriorityRecommendationRationaleImplementation SketchCritical (P1)Migrate Proxy Admin to a DAO‑controlled Multi‑Sig (≥3‑of‑5)Removes single‑key upgrade authority, aligning upgrade path with governance decisions.Deploy a newProxyAdmincontract owned by a Gnosis Safe (or similar) with the DAO as the sole executor. Transfer ownership viachangeAdmin.Critical (P1)Add “Snapshot‑At‑Execution” Quorum CheckPrevents front‑running after quorum is met and tokens are sold.Extend timelockexecuteto read the voting snapshot stored at proposal creation and reject execution if current voting power < required quorum.High (P2)Cap Delegated Voting Power per Address (e.g., 5 % of total supply)Limits concentration of voting power and mitigates token‑whale dominance.Modify delegation contract to enforce a per‑address cap; add a governance‑controlled parameter to adjust the cap.High (P2)Restrict Timelockexecuteto a whitelist of approved target contractsPrevents arbitrary delegatecalls that could upgrade core contracts without DAO oversight.Introduce atargetWhitelistmapping in the timelock; only allow execution iftarget∈ whitelist. Governance can add/remove entries via a dedicated proposal.High (P2)Introduce Flash‑Loan Guard on Voting SnapshotsStops temporary vote‑buying via flash loans.Record the block number of each snapshot; reject votes from addresses whose balance changed within the lastNblocks (e.g., 10).Medium (P3)Raise Governance Quorum to ≥ 25 %Increases the cost of collusion and reduces risk of low‑participation attacks.Update the DAO’s quorum parameter; enforce via the same snapshot‑at‑execution check.Medium (P3)Increase Proposal Creation Fee to ≥ 1 % of TVL (or a fixed $10k minimum)Discourages spam proposals and raises the economic barrier for DoS attacks.Add a fee‑validation step in the proposal‑creation function; fee sent to a burn address or DAO treasury.Medium (P3)Add Explicit Event Emission for All Governance‑Sensitive State ChangesImproves on‑chain observability and enables third‑party monitoring bots.EmitFeeParametersUpdated,BridgeConfigChanged, etc., with full parameter payloads.Low (P4)ApplynonReentrantGuard to ERC‑1155 Hooks in Liquidity PoolsEliminates a niche re‑entrancy vector without affecting performance.WraponERC1155ReceivedandonERC1155BatchReceivedwith OpenZeppelin’sReentrancyGuard.Low (P4)Separate Bridge Governance from Core DAOReduces blast‑radius if L1 governance is compromised.Deploy a dedicated “Bridge DAO” with its own timelock (e.g., 72 h) and a subset of voting power; require cross‑DAO approval for critical bridge actions.
WeekMilestone1‑2Deploy Multi‑Sig
Implementation Timeline (Suggested)ProxyAdmin; transfer admin rights.2‑3Add snapshot‑at‑execution check & quorum increase.3‑4Deploy updated delegation contract with voting‑power caps.4‑5Introduce timelock target whitelist and flash‑loan guard.5‑6Adjust proposal fee schedule and emit new events.6‑8Conduct a full governance‑upgrade rehearsal on a testnet (e.g., Sepolia + Arbitrum Sepolia).8‑10Deploy Bridge‑DAO separation (if deemed necessary).OngoingContinuous monitoring, bug‑bounty integration, and community education.4. Risk Score
DimensionScore (1‑10)CommentsGovernance Token Concentration8Large holder + unlimited delegation creates a “single‑point‑of‑failure”.Upgradeability & Timelock Controls7Admin key is single‑sig; timelock permits arbitrary calls.Cross‑Chain Bridge Coupling6Bridge parameters governed by same DAO; no L2‑specific safety.Economic Attack Vectors (Flash‑Loan, Spam)5Low barriers to vote‑buying and proposal spam.Overall Composite Risk7 / 10Moderate‑to‑high risk; mitigations can reduce to ≤ 4 with timely execution.
Scoring methodology follows the standard DeFi risk matrix (Impact × Likelihood, normalized to 1‑10).
5. Conclusion
The Spark Liquidity Layer’s governance framework is functional but exposes a sizable attack surface due to centralized token holdings, unrestricted upgrade pathways, and insufficient quorum enforcement. While the protocol’s core liquidity contracts are relatively well‑engineered, the governance layer is the weakest link and could be leveraged to compromise the entire $2.7 B TVL.By migrating upgrade authority to a DAO‑controlled multi‑sig, hardening the timelock execution path, capping delegated voting power, and raising quorum and proposal‑creation costs, the protocol can significantly lower its risk profile (target composite score ≤ 4). These changes are technically straightforward, have minimal impact on user experience, and align with best practices observed in leading DeFi projects (e.g., MakerDAO, Aave, Uniswap).
We recommend immediate execution of the Critical (P1) recommendations followed by a staged rollout of the remaining mitigations. A post‑implementation audit should be performed to verify that the governance attack surface has been reduced to an acceptable level before any further TVL growth or L2 expansion.
Prepared for the Spark Liquidity Layer DAO. All findings are based on publicly available contracts (Etherscan, Sourcify) and the latest audited source code (v2.3.1, 2026‑09‑15). The reviewer remains available for a walkthrough, Q&A session, or deeper code‑level audit upon request.
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I Love Israel: Defense Manufacturer Elbit Systems Acquires Canadian Underwater Drone Company
Elbit Systems, the international military technology company and defense contractor based in Israel, recently announced its successful acquisition of the Canadian advanced autonomous underwater firm Submarine Engineering Ltd. (ISE), according to a news report by The Jerusalem Post. This breakthrough strengthens Elbit Systems’ underwater surveillance, mine countermeasures and anti-submarine warfare capabilities.
To put things in perspective, posted below is an excerpt from The Jerusalem Post report. Some parts in boldface.
Israeli defense manufacturer Elbit Systems Ltd. completed the acquisition of Canada-based advanced autonomous underwater company International Submarine Engineering Ltd. (ISE), the company announced on Tuesday.
Elbit said the “acquisition was completed for a purchase price that is not material,” which means it was not a notable amount of money.
ISE specializes in advanced autonomous underwater and remotely operated systems for the maritime domain, which Elbit described as a “high-technology company engaged in the development and manufacture of undersea vehicles, including Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs), as well as computer control systems and robotics.”
“Elbit Systems delivers proven naval capabilities supporting missions ranging from coastal security to blue-water operations,” the company said.
Acquisition of Canadian naval drone company boosts Elbit’s underwater capabilities – “The addition of ISE’s underwater autonomous technologies is intended to expand Elbit Systems’ capabilities in underwater Intelligence, Surveillance and Reconnaissance (ISR), Mine Counter-Measures (MCM) and Anti-Submarine Warfare (ASW), further strengthening the company’s end-to-end maritime offering,” Elbit added.
“With more than 50 years of experience in subsea robotics, ISE has delivered over 250 underwater vehicles to customers in more than 20 countries worldwide,” Elbit said.
The Israeli defense giant’s naval portfolio includes “unmanned surface vessels, underwater systems, integrated command-and-control (C2) suites, electro-optical and sonar systems, communications, and electronic warfare technologies.”
“This acquisition marks another milestone in Elbit Systems’ strategy to expand its offerings in the naval domain. Combined with our existing capabilities in naval electronic warfare, autonomous systems, naval precision munitions and maritime mission systems, ISE’s underwater technologies will further strengthen our position as a global provider of comprehensive, integrated maritime solutions,” said President and CEO of Elbit Systems, Bezhalel “Butzi” Machlis.
To all my readers, I encourage you to thank the Lord for this tremendous breakthrough. Elbit Systems’ acquisition of International Submarine Engineering is very crucial for a variety of reasons.
At the same time, I encourage you all to realize the truth that Israel is the land God designated specifically for the Jewish people (read Genesis 35:10-12) and His command must be followed without hesitation. If you want to be blessed further by the Lord, do so by loving and blessing the Jewish people (Genesis 12:1-3). I did my part when I was in Israel. Also, let me remind you all that the ties between the Jews and Christians are truly biblical!
I encourage you all to pray to the Lord God in support of Israel, to love and bless the Jewish people, and pray for the peace of Jerusalem.
If you truly believe in Lord Jesus, the Holy Spirit and God the Heavenly Father wholeheartedly and you continue to be faithful, you should be aware that Christians are meant to stand united with Israel and love the Jewish people no matter what. You can do your part supporting Israel by donating to Christians United for Israel (CUFI). Do not forget to read the Holy Bible, then pray in tongues to the Lord in the privacy of your room with the door shut.
Always be the fearless and aggressive church of Lord Jesus!
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An AI coding agent’s overall accuracy score can hide where it helps—and where it creates more review work. Evaluate agents by task category, define acceptance criteria in advance, and track outcomes beyond whether a pull request is accepted.
A study of 7,156 pull requests offers a useful example of why this matters. The paper Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance compared five agents across nine task categories over 32 weeks.
Why task category belongs in the evaluation
The study reported an 82.1% acceptance rate for documentation tasks and 66.1% for new-feature tasks—a difference of about 16 percentage points. That gap was larger than the typical difference between agents in many categories.A single blended score can therefore obscure important differences. An agent that is useful for documentation may not be the right choice for feature work, where requirements interpretation, dependencies, and testing create more ways for a change to miss its intended behavior.
Acceptance rate is a useful outcome, but it does not measure code quality, security, maintainability, or developer productivity on its own. Treat it as one signal in a broader evaluation.
What the study found about individual agents
The results did not identify one universal winner. OpenAI Codex had consistently strong results across all nine categories, with acceptance rates ranging from 59.6% to 88.6%; the paper also reported statistically significant advantages over other agents in several categories.Category leaders varied: Claude Code led documentation at 92.3% and performed best on feature tasks in the reported results, while Cursor led the fix category at 80.4%. Devin was the only agent with a consistent positive acceptance trend during the 32-week period, increasing by 0.77% per week. The other agents were described as largely stable.
These are historical results from one dataset and time window. Use them to shape questions for your own evaluation, not as a substitute for testing against your repositories and review standards.
Build a task-stratified evaluation
1. Choose categories that reflect your work
Separate evaluation sets for documentation, bug fixes, feature work, refactoring, testing, and other relevant tasks. Start with the categories that make up your intended use case. Keep results separate by category rather than combining every pull request into one score.2. Make tasks assessable
For each task, state the objective, boundaries, relevant files or services, expected behavior, and validation requirements. Keep requirements connected to the implementation and test evidence so reviewers can judge whether the change meets the original intent.Feature work warrants particular care: the study’s 66.1% acceptance rate for new features was lower than the documentation result. Clear requirements, linked work items, assigned review ownership, and test evidence help make these changes easier to assess. Provide a way to revise rejected changes rather than treating rejection as the end of the process.
3. Track more than acceptance
Record acceptance rate by task category, but also capture review time, rework, escaped defects, test failures, and how much human editing was needed before acceptance. These measures help distinguish an accepted change that required substantial correction from one that was ready with little revision.4. Preserve evaluation context
Record the agent and version, task category, repository context, and acceptance criteria for each evaluation. Repeat the benchmark periodically: models, prompts, repository conventions, and review practices can change, so results may not remain comparable without this context.Turn results into delivery controls
- Classify the intended work. Decide which task categories are in scope and review results separately for each.
- Set quality gates. Specify required tests, reviewers, security checks, and documentation before expanding agent use.
- Keep work traceable. Link requests, requirements, implementation, reviews, and outcomes so the team can investigate failures.
- Compare total effort. Consider review time, revisions, rejected pull requests, and post-release issues alongside acceptance.
- Reassess regularly. Repeat measurements when agents, repositories, or internal practices change.
The practical takeaway is to select and govern coding agents at the task level. The study’s category differences show why a broad ranking can mislead; a local benchmark, explicit acceptance criteria, and ongoing measurement give teams a more useful basis for deciding where an agent fits.#ai #devtools #softwareengineering #testing #software #coding #development #engineering #inclusive #community
Evaluate AI Coding Agents by Task, Not by One Score -
DATE: October 22, 2026 at 06:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Brain scans suggest first graders don’t engage their control networks like adults when talking to ChatGPT
A small brain imaging study suggests that young children show less communication within and between the brain networks responsible for self-regulation and focused attention when brainstorming with an artificial intelligence chatbot than adults do. Although first graders and adults scored similarly, relative to their age groups, on a standard test of creative thinking outside the brain scanner, only adults showed a link between higher creativity and stronger coordination among these mental control systems during the conversation. The findings, published in Cerebral Cortex, suggest that young children may not yet have the mature brain wiring needed to actively direct and evaluate a collaborative conversation with generative artificial intelligence.
Generative artificial intelligence programs, such as ChatGPT, are powered by large language models, which are computer systems trained on massive amounts of text to predict how words fit together, allowing them to produce human-like responses and brainstorm ideas in real time. As these tools enter homes and elementary classrooms, children are increasingly using them for storytelling and collaborative problem-solving, a process known as co-creativity. Keeping up with a fast-talking, unpredictable digital partner requires cognitive control, which is the mind’s ability to plan ahead, stay focused on a goal, remember what was already said, and filter out unhelpful distractions.
Generating original and useful ideas relies heavily on how different systems in the brain communicate with one another. For instance, a 2018 neuroimaging study of adults (covered by PsyPost at the time) indicated that people who come up with more original ideas tend to have stronger synchronization among three major brain networks: one involved in spontaneous daydreaming and memory, another that flags important new thoughts, and a third that handles cognitive control and goal-directed planning. Instead of operating separately, these systems team up so a person can both brainstorm freely and judge whether an idea actually makes sense.
In young children, however, the brain networks that manage cognitive control and focused attention are still under construction, only reaching full maturity in a person’s mid-twenties. A 2019 neuroimaging study of young children, conducted by the same research group behind the new study, found that across children ranging from 17 months to nine years old, older children tended to show stronger connections within and between their cognitive control networks while listening to stories. In addition, a neuroimaging study covered by PsyPost in 2023 indicated that the way cognitive control networks relate to creative thinking shifts across development, with stronger connectivity in these control regions linked to higher creativity in adolescents but lower creativity in adults.
First grade, around ages six and seven, is a sensitive developmental window when children are first learning to evaluate text and speech on their own, while still tending to trust perceived experts and technology without much skepticism. The research was led by Tzipi Horowitz-Kraus, an associate professor with the Educational Neuroimaging Group in the Faculty of Education in Science and Technology and the Faculty of Biomedical Engineering at the Technion – Israel Institute of Technology, who is also affiliated with the Kennedy Krieger Institute and Johns Hopkins University School of Medicine.
She and her Technion colleagues Yoed Kenett, Dafna Link-Sourani, Emeel Ashqar, and Rola Farah examined whether first graders engage their cognitive control and attention networks to the same degree as adults when brainstorming with ChatGPT, and how that brain activity relates to their underlying creative ability. Part of the motivation came from a 2025 preprint, which has not been peer reviewed, in which adults who wrote essays with ChatGPT showed less coordinated brain activity than those who used a search engine or no tools at all.
“Generative AI is entering children’s lives, and classrooms, much faster than the evidence about how young brains engage with it,” Horowitz-Kraus told PsyPost. “Studies in adults have suggested that people recruit fewer cognitive resources when they work with ChatGPT, but adults have mature cognitive control systems, and these systems keep developing into the mid-twenties. We focused on first graders (ages 6–7) because this is when formal schooling begins, when executive functions are developing rapidly, and when children tend to place a great deal of trust in sources they perceive as experts. We wanted to know what the brain of a young child is actually doing during a real conversation with ChatGPT, compared with an adult given exactly the same task.”
To investigate this, the researchers recruited 15 first-grade children with an average age of about 6.4 years and 16 adults with an average age of about 38 years. All participants came from average to above-average socioeconomic backgrounds, had no history of neurological or psychiatric conditions, and completed standard tests to confirm typical verbal and nonverbal intelligence. Before entering the brain scanner, each participant took a behavioral creativity test called the Divergent Association Task, which asks a person to name 10 words that are as unrelated in meaning as possible.
Inside a functional magnetic resonance imaging (fMRI) scanner, which measures brain activity by tracking changes in blood flow, participants engaged in a five-minute spoken conversation with ChatGPT. Using a specialized microphone and noise-canceling audio system built for the scanner, both children and adults were given the same open-ended goal: they had to plan the opening of any kind of store they wanted, anywhere and for anyone, by consulting out loud with ChatGPT. Immediately before the scan began, children were told they would be speaking to “the smartest computer in the world,” also known as ChatGPT, whereas adults were simply told they would be speaking to ChatGPT.
“I would also like to note that holding a live spoken conversation with ChatGPT inside an MRI scanner, with six-year-olds, required dedicated infrastructure developed at the Technion Human MRI Research Center,” Horowitz-Kraus noted. “I am very grateful to the children, parents and students who took part.”
The researchers recorded and transcribed every conversation to measure how original and varied the spoken exchanges were. They used a computer model to calculate a “divergent semantic integration” score, which measures how far apart the meanings of all the words in a conversation are from one another; for example, the words “cat” and “democracy” sit much farther apart in meaning than “cat” and “dog.” On the brain scans, the team measured functional connectivity, which reflects how closely different brain regions synchronize their activity over time, across seven major brain networks after statistically controlling for head movement inside the scanner.
These seven systems included the frontoparietal and cingulo-opercular networks, which manage cognitive control and task goals; the dorsal and ventral attention networks, which handle voluntary focus and automatic reactions to new information; the salience network, which acts as a switchboard by detecting important ideas; the default mode network, which supports spontaneous imagination; and the memory retrieval network.
On the word-association creativity test taken outside the scanner, children and adults scored at comparable levels relative to others their age, with average percentile scores of 28.61 and 26.16, respectively, a difference that was not statistically significant. During the actual five-minute conversation with ChatGPT, however, adults produced slightly more diverse and wide-ranging spoken narratives than the children did, scoring an average of 0.82 on the semantic integration measure compared to 0.81 for the first graders, a small difference that was nonetheless statistically reliable.
When the researchers examined the brain scans, they found pronounced differences in how the two age groups engaged their mental control and attention systems while talking to the chatbot. Within individual brain networks, adults showed substantially stronger internal synchronization in the frontoparietal control network, where adults averaged a connectivity score of 0.201 compared to 0.113 in children. Adults also had higher internal connectivity in the salience network (0.289 versus 0.198 in children) and the dorsal attention network (0.211 versus 0.162 in children). Only the frontoparietal difference held up after the researchers adjusted for the number of comparisons they ran.
In contrast, internal connectivity within the default mode network, which handles spontaneous imagination, did not differ between the two groups, averaging 0.187 in adults and 0.181 in children. Communication across different brain networks was also more integrated in adults than in first graders during the AI conversation. After adjusting for multiple statistical comparisons, the most robust difference appeared in how the frontoparietal control network linked up with the dorsal attention network (averaging 0.126 in adults versus 0.039 in children).
Before correcting for multiple comparisons, adults additionally showed stronger cross-network ties linking memory retrieval regions to cognitive control and attention systems, as well as stronger coupling between the default mode network and memory retrieval (0.150 in adults versus 0.111 in children). The researchers then tested whether a person’s baseline creativity score outside the scanner predicted how strongly their brain networks communicated while using ChatGPT.
They found that in adults, higher creativity scores were positively linked to stronger communication between the frontoparietal control network and the salience network during the AI dialog. Among the first graders, however, baseline creativity showed no statistically significant relationship with the strength of these brain network connections. That adult pattern differs from the 2023 study described earlier, which tied stronger connectivity within the executive control network to lower creativity in adults, though that study looked at connections within a single network rather than links between networks.
“Two things” surprised the team, Horowitz-Kraus explained. “First, children and adults looked similar in creative ability on the standard test, yet the neural route they took during the conversation was quite different; the difference lay in how creativity is implemented in the brain, not in baseline capacity. Second, the default mode network, which is central to most models of creativity, did not differ between the groups. One possible explanation is that conversing with ChatGPT in a scanner was novel for everyone, but that needs to be tested directly.”
Taken together, the results suggest that even when young children have age-appropriate creative potential, they engage their control, attention, and memory systems in a less integrated way than adults do during a conversation with generative AI. The authors propose that adults use their salience and frontoparietal networks to filter ChatGPT’s rapid responses and steer the brainstorming toward their goal, a role these networks may not yet play in six- and seven-year-olds.
“Talking to a chatbot looks effortless, but it draws on planning, monitoring, attention and memory systems that are still under construction in a six-year-old, which is why adult guidance matters when young children use these tools,” Horowitz-Kraus said.
“The practical message is that young children should not be left to use generative AI on their own,” she added. “For parents and teachers, this means sitting with the child, asking questions about the answers, and treating the AI as a shared activity instead of an independent tutor. For educators, pediatricians and policy makers, it means that the age at which children start using these tools deserves the same careful attention we already give to screen exposure. This study cannot set a specific ‘safe age’ since it focused on two very distinct age groups, but it is a clear signal that tools designed around adult abilities should not simply be handed to young children.”
There are a few things to keep in mind when interpreting these findings. Because the study did not include a comparison task where participants brainstormed on their own or talked with a human partner inside the scanner, the design cannot separate general age differences in brain maturity from effects caused specifically by ChatGPT. In other words, the lower network connectivity seen in children may reflect how six-year-old brains handle this kind of complex task in general, rather than showing that ChatGPT actively suppresses or harms their brain activity.
“This study does not show that ChatGPT reduces cognitive control in children or harms their brains,” Horowitz-Kraus emphasized. “We compared children with adults doing the same ChatGPT task; we did not compare children with and without ChatGPT, or ChatGPT with a human conversation partner. So we cannot yet separate what is specific to AI from general developmental differences in how the brain handles this kind of conversation.”
The way the chatbot was introduced may have also influenced how the children behaved. Telling first graders that they were about to talk to “the smartest computer in the world” may have encouraged them to passively accept the machine’s suggestions rather than questioning or evaluating its ideas, which could naturally lower their use of cognitive control networks. Future research will need to give children and adults the exact same instructions, or intentionally test how calling an AI an “expert” changes how critically kids think.
In addition, the sample size of 15 children and 16 adults was relatively small, and the groups were unevenly split by sex, with 11 boys among the 15 children and four men among the 16 adults. The study had enough participants to detect large differences between age groups, but the analyses linking creativity to brain connectivity were exploratory and likely underpowered.
The researchers also did not control for differences in everyday vocabulary size, how fast participants spoke, how many turns they took in the conversation, or how much prior experience they had with ChatGPT before the experiment (and adults likely had far more experience with the tool). Tracking children over several years in larger studies will help educators and pediatricians determine the developmental stage at which kids build the mental control needed to actively collaborate with artificial intelligence tools.
“The next steps are larger samples, a direct comparison of talking with ChatGPT versus talking with a human partner or working without AI, and longitudinal follow-up to identify when in development the control networks begin to engage in an adult-like way and to relate to creativity,” Horowitz-Kraus said. “We also plan to measure children’s familiarity with AI and to test how the perceived authority of the AI shapes their engagement. The long-term goal is to give educators, pediatricians and policy makers evidence for developmentally appropriate use of generative AI, in the same way that guidance exists for screen exposure.”
“Technology can support learning, but it cannot lead it; children learn best alongside an adult who guides and challenges them,” she added.
The study, “Lower engagement of cognitive control in children on ChatGPT,” was authored by Tzipi Horowitz-Kraus, Yoed N. Kenett, Dafna Link-Sourani, Emeel Ashqar, and Rola Farah.
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DATE: October 24, 2026 at 12:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Emotional struggles are linked to vulnerable narcissism but not grandiose narcissism, meta-analysis finds
A new statistical review of data from more than 12,000 adults suggests that difficulties with managing emotions are moderately linked to one specific form of narcissism, while showing virtually no connection to another. The research, published in Personality and Individual Differences, indicates that people with insecure and defensive narcissistic traits tend to struggle with emotional control, whereas those with more boastful, dominant narcissistic traits generally do not report these same struggles. These findings help clarify why past studies on narcissism and emotional health have produced conflicting results, and they may point to specific emotional skills that could be targeted in therapy.
In psychology, trait narcissism refers to a persistent pattern of personality characteristics centered on interpersonal antagonism, which includes feeling entitled, manipulating others, and lacking empathy. Rather than being a single uniform trait, narcissism is generally divided into two main subtypes: grandiose and vulnerable. Grandiose narcissism matches the common stereotype of a narcissist, featuring an outgoing, dominant, attention-seeking, and aggressively self-confident style. Vulnerable narcissism, while sharing the same core of entitlement and self-centeredness, looks very different on the surface, involving introversion, fragile self-esteem, deep feelings of inadequacy, and a heightened sensitivity to rejection.
Both forms of narcissism are associated with problems in relationships, including a lack of care for a partner’s distress, relationship dissatisfaction, and even intimate partner violence; a 2024 meta-analysis found that violence was more strongly tied to vulnerable narcissism (a correlation of 0.25) than to grandiose narcissism (0.11). Because personality traits themselves are deeply ingrained and difficult to change, psychologists often look for modifiable behaviors and skills that might help improve how narcissistic individuals function in daily life. One promising target is emotion dysregulation, which refers to difficulty understanding, managing, and responding to feelings in a healthy way that aligns with a person’s goals and social norms.
“Our broader interest in this area stems from wanting to understand the psychological factors that contribute to the interpersonal difficulties experienced by people with high levels of narcissism,” senior author Megan L. Willis, an associate professor in the School of Behavioural and Health Sciences and the Healthy Brain and Mind Research Centre at Australian Catholic University, told PsyPost. “I’m particularly interested in factors that may be modifiable – that is, things that we may be able to prevent or improve through psychological intervention.”
When psychologists study emotion dysregulation, they often look at several distinct areas where a person’s emotional control can break down. These areas include refusing to accept negative feelings, lacking awareness or clarity about what emotion is actually occurring, struggling to stay focused on tasks when upset, failing to control impulsive behaviors during distress, and lacking effective strategies to calm down. Studies linking narcissism to these emotional difficulties have produced confusing results, with some finding that narcissistic people had worse emotional control and others finding no link or even better emotional control.
Psychologists began to suspect that these contradictions happened because studies were measuring different subtypes of narcissism. For instance, a 2017 study of Chinese university students found that students with vulnerable narcissistic traits reported substantial trouble managing their emotions, while those with grandiose traits actually reported fewer emotional difficulties, which the authors linked to their higher self-esteem. Similarly, a 2020 study of undergraduates indicated that the defensive, self-protective side of narcissism was tied to poor emotion recognition and messy emotional reactions, whereas the assertive, self-promoting side was linked to better emotional management.
To make sense of the growing body of research, a 2024 systematic review summarized the existing literature and observed a consistent link between vulnerable narcissism and emotional struggles, alongside a lack of evidence connecting grandiose narcissism to those same struggles. However, that earlier review only summarized the studies qualitatively rather than mathematically combining their data, and it mixed psychiatric patients with the general public, which can weaken the correlations researchers observe. Willis, lead author Ria Tziliaskopoulos, and their colleagues at Australian Catholic University set out to conduct a full meta-analysis, a statistical technique that pools data from multiple studies to estimate the strength of the relationship between narcissism and emotion dysregulation in the general adult population.
“We wanted to establish the strength of the relationship between emotion dysregulation and narcissism in general, as well as determine whether this relationship differed between grandiose and vulnerable narcissism,” Willis explained.
The researchers searched five major academic databases through January 2026 to find studies written in English that measured both trait narcissism and emotion dysregulation in adults outside clinical settings. They excluded studies focusing on children or specialized groups like psychiatric patients or prison inmates, ensuring the results would reflect everyday adult populations. This screening process yielded 26 eligible studies from 25 reports, encompassing a combined total of 12,209 participants with average ages ranging from 18.7 to 62 years across countries including the United States, Italy, Turkey, China, Iran, and Brazil.
Because each included study used questionnaires to measure personality and emotional habits, the authors categorized the narcissism questionnaires into three groups: those measuring grandiose narcissism, those measuring vulnerable narcissism, and “combined” measures that blended both traits into a single score. For instance, the widely used Narcissistic Personality Inventory counted as a grandiose measure and the Hypersensitive Narcissism Scale as a vulnerable one, while the 2020 undergraduate study’s self-promoting “admiration” scale was counted as grandiose and its defensive “rivalry” scale as vulnerable.
Twenty-two of the 26 studies measured emotional difficulties using a standard questionnaire called the Difficulties in Emotion Regulation Scale, which scores both overall dysregulation and the six specific problem areas like impulse control and emotional awareness. The researchers extracted 80 individual statistical correlations from the 26 studies and used a method called robust variance estimation to account for the fact that several studies contributed multiple data points from the same group of people.
In statistical terms, a correlation ranges from -1 to 1, where 0 means no relationship, positive values mean two traits tend to rise together, and negative values mean one tends to fall as the other rises. By common convention, values of about 0.10 to 0.29 are considered weak, 0.30 to 0.49 moderate, and 0.50 or above strong. When the researchers pooled all 80 data points together without separating the narcissism subtypes, they found a weak positive correlation of 0.15 between overall narcissism and emotion dysregulation. This meant that across the entire dataset, higher levels of narcissism were only slightly associated with greater trouble managing emotions.
When the team broke the data down by narcissism subtype, a sharp divide emerged that helps explain why the overall correlation was so small. Vulnerable narcissism showed a moderate positive correlation of 0.37 with emotion dysregulation across 11 studies. In contrast, grandiose narcissism showed a correlation of 0.04 across 21 studies, a number so close to zero that it was not statistically significant.
“The relationship with vulnerable narcissism was moderate in size, which is quite a meaningful relationship in individual differences research,” Willis noted. “Narcissism reflects a cluster of personality traits, so we wouldn’t expect any single psychological factor to explain it. The size of the relationship suggests that difficulties regulating emotions are an important part of the psychological profile of people high in vulnerable narcissism.”
Measures that combined both forms of narcissism fell right in the middle, showing a weak positive correlation of 0.25 across five studies. Follow-up statistical comparisons confirmed that the link between vulnerable narcissism and emotional difficulties was substantially stronger than the link for grandiose narcissism. The authors also checked whether a few debatable coding choices drove the results. Dropping the grandiose scale of the Pathological Narcissism Inventory, which critics say overlaps too much with vulnerable traits, left grandiose narcissism at 0.03, and dropping the one study that counted the defensive “rivalry” scale as vulnerable narcissism left vulnerable narcissism at 0.37.
“The findings may help explain some of the interpersonal difficulties experienced by people high in vulnerable narcissism,” Willis said. “They tend to be hypersensitive to rejection and criticism, and our findings suggest they are also more likely to have difficulty regulating their emotions. When they feel rejected or criticized, they may struggle to manage the emotions that arise in these situations. This could contribute to hostile or aggressive responses, which can create conflict and damage their relationships with others.”
The researchers then examined the four or five studies that reported scores for each of the six domains of emotional difficulty, pooling all types of narcissism together. They found weak but statistically reliable correlations with three specific problem areas: limited access to effective emotion regulation strategies had a correlation of 0.21, trouble controlling impulses when upset had a correlation of 0.19, and refusing to accept negative emotions had a correlation of 0.18. Meanwhile, narcissism was not statistically linked to lacking emotional awareness (which had a slight negative correlation of -0.08), lacking emotional clarity (0.13), or struggling to focus on goal-directed behaviors when distressed (0.13). The link with emotional awareness was weaker than the link with every other domain.
The authors suggest this pattern means the emotional struggles tied to narcissism may be less about failing to notice feelings and more about how a person reacts once an unpleasant emotion arrives, such as struggling to accept the feeling, acting impulsively, or feeling there is no healthy way to calm down. Because these analyses drew on only a handful of studies and combined all forms of narcissism, they cannot show whether the pattern differs between grandiose and vulnerable traits. The authors note that these specific breakdowns could help explain why people high in narcissism may lash out, blame others, or withdraw during relationship conflicts.
These results align with a study covered by PsyPost in 2024, which also found that emotion dysregulation was tied to vulnerable rather than grandiose narcissism, although that earlier study tested psychiatric outpatients rather than the general adult samples analyzed in the new review.
The findings sit in partial tension with the 2020 study of undergraduates described earlier, which PsyPost covered in 2019, where the self-promoting side of grandiose narcissism was linked to fewer emotional difficulties and better emotional awareness. The meta-analysis included that study but counted its defensive rivalry scale as vulnerable narcissism, and across all the grandiose questionnaires combined, it found no link either way rather than a protective one.
The absence of a link for grandiose narcissism also contrasts with research covered by PsyPost earlier in 2026, which tied both grandiose and vulnerable traits to brain differences connected to hiding one’s feelings. That difference may reflect what was measured: the brain study looked at the specific habit of suppressing outward emotional expressions, while the meta-analysis assessed broader difficulties managing emotions.
As with all research, there are some caveats to keep in mind when interpreting these findings. Every study included in the meta-analysis relied on self-report questionnaires, which depend on participants being both honest and self-aware about their flaws. The authors point to a 2023 study that recorded facial muscle activity and found amplified emotional reactions to negative social evaluation among people with grandiose traits, suggesting questionnaires may miss some of their emotional responses.
“I also wouldn’t interpret the lack of a relationship with grandiose narcissism as definitive evidence that people high in grandiose narcissism don’t experience difficulties regulating their emotions,” Willis cautioned. “All of the studies relied on self-report measures, and people high in grandiose narcissism may be less likely to perceive or report difficulties with emotion regulation.”
All 26 studies also used cross-sectional designs, measuring personality and emotional habits at a single point in time. In addition, half of the studies (13 of 26) recruited only university students, and most were conducted in Western nations, meaning the findings may not apply equally to older adults or different cultural contexts.
“The main caveat is that all of the studies included in our meta-analysis were cross-sectional, so we can’t determine the direction of the relationship,” Willis said. “Difficulties regulating emotions may contribute to the development or maintenance of vulnerable narcissism, vulnerable narcissism may contribute to difficulties regulating emotions, or other factors may explain this relationship.”
One such shared factor the authors raise is early experience: vulnerable narcissism has been theorized to arise partly from childhood trauma or inconsistent parenting, which may also hinder the development of emotional skills. Results also varied widely from study to study, so the pooled correlations are best read as averages rather than as figures that apply equally to every group or questionnaire. Several statistical checks did suggest the findings were unlikely to be skewed by publication bias, the tendency for studies with positive results to be published more often.
Another limitation is that too few studies reported detailed breakdowns of the six emotional problem areas to allow the authors to test grandiose and vulnerable narcissism separately for each specific skill. The authors recommend that future studies routinely report data for all individual emotion regulation subscales alongside total scores, use longitudinal designs that follow people over time, and recruit more diverse samples across cultures and age groups. Even with these limitations, the authors suggest that therapies focused on emotion regulation, such as dialectical behavior therapy or schema therapy, may be worth testing for people high in vulnerable narcissism, though studies have yet to show whether such treatment improves their well-being or relationships.
Looking ahead, the research team is now examining the roots of these traits and how emotional habits take shape over time. In psychology, insecure attachment refers to relationship patterns characterized by anxiety or avoidance that often stem from inconsistent caregiving early in life.
“One of the things I’m particularly interested in now is understanding how vulnerable narcissism may develop,” Willis told PsyPost. “We’re currently testing models looking at the potential role of insecure attachment and difficulties identifying, understanding and regulating emotions. Ultimately, we want to identify potentially modifiable factors that could be targeted through prevention or intervention strategies.”
The study, “The relationship between narcissism and emotion dysregulation: A systematic review and meta-analysis,” was authored by Ria Tziliaskopoulos, Rose Ferguson, Wendy Song, and Megan L. Willis.
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DATE: October 23, 2026 at 02:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: College-educated people aren’t Big Tech’s biggest fans. They’re its most conflicted, study suggests
Public opinion toward major technology corporations does not fall neatly along a simple spectrum from support to opposition, according to new research published in Research and Politics. Analyzing survey data from six countries, researchers found that higher levels of education are linked to mixed, conflicted views rather than outright enthusiasm for large tech firms. The study also indicates that political ideology is linked to these attitudes in distinct ways, with left-leaning individuals more likely to be skeptical and highly educated right-leaning individuals increasingly likely to hold ambivalent views.
Big Tech refers to the largest and most dominant companies in the information technology industry, specifically global corporations such as Google, Apple, Meta, Amazon, and Microsoft. Beyond selling consumer products and digital services, these firms control the core infrastructure of modern communication, commerce, and emerging tools like artificial intelligence. Because their platforms influence how citizens find information, participate in public debates, and interact with democratic institutions, governments face growing questions about whether to regulate these companies more strictly or support their continued growth.
Political scientists have spent considerable effort examining how technological shifts affect workers and voters, though less attention has gone toward how the public evaluates the specific corporations driving those changes. For example, a 2022 review noted that workplace automation and digitalization tend to divide the workforce into economic winners who favor the political status quo and routine workers who face job risks and gravitate toward populist politics. Similarly, a study covered by PsyPost in 2022 found that workers facing higher exposure to job automation were more likely to support radical-right parties and report lower satisfaction with democracy.
When turning from workplace technology to the specific corporations behind it, Tobias Tober and colleagues at the University of Konstanz expected education and political ideology to guide public attitudes. In modern knowledge economies, which rely heavily on information and technical expertise rather than manual labor, university-educated individuals usually enjoy stronger job prospects and greater familiarity with digital tools. Prior work, including a 2024 cross-country survey, conducted in part by two of the same researchers, linked how much job risk people perceive from digitalization to how they want governments to respond. Based on these patterns, the authors initially expected highly educated people to view Big Tech companies positively.
Ideology was also expected to play a central role, though in different ways across the political spectrum. Individuals on the political left generally distrust corporate monopolies, wealth inequality, and unchecked private power, which suggests they would view tech giants critically. On the political right, expectations are more complicated because traditional pro-business values favor large corporations, whereas right-wing populist movements often distrust the cultural and social shifts tied to digital capitalism.
To test how these factors work in practice, the researchers commissioned the survey firm Kantar Public to collect data in June and July 2022 across six countries: Germany, Japan, Poland, Spain, Sweden, and the United States. The sample included 3,300 adults aged 18 to 64 in each country, totaling 19,800 respondents. The researchers used quota sampling for age, gender, and education so that the participants reflected the broader national populations of their respective countries.
Participants rated their agreement on a five-point scale with six statements about the societal role of global technology companies like Amazon, Apple, Google, Facebook, and Microsoft. Three statements reflected positive contributions: providing useful services to the public, promoting innovation and economic development, and aiding democracy by offering a digital space for open debate. The other three statements captured negative impacts: undermining the national welfare state by avoiding taxes, weakening labor standards, and becoming so powerful that they threaten democracy.
The researchers then used exploratory factor analysis, a statistical technique that groups related survey answers together to uncover underlying patterns in how people think. Rather than finding a single scale where positive views sit at one end and negative views sit at the other, the analysis pointed to two separate dimensions that barely correlated with each other. Agreeing with positive statements about Big Tech had almost no bearing on whether a person disagreed with negative statements.
Next, the authors applied a grouping method called k-means cluster analysis to see how respondents combined these positive and negative evaluations. The researchers sorted the 19,800 participants into five profiles. The largest group was the neutral cluster (8,140 respondents), consisting of people who neither agreed nor disagreed with most statements, followed by the ambivalent cluster (5,114 respondents), who agreed with both positive and negative statements at the same time.
The remaining participants fell into three smaller categories. Big Tech supporters (3,739 respondents) agreed with the positive statements and rejected the negative ones, while skeptics (2,123 respondents) endorsed the negative statements and rejected the positive ones. Finally, a small dismissive group (685 respondents) disagreed with both positive and negative characterizations of the industry.
To see how education and ideology predicted membership in these five groups, the team ran statistical models that accounted for income and differences between countries, and the results held when they also accounted for technology use at home and at work. Education was divided into three levels based on international standards, ranging from lower secondary schooling up to university degrees. Political ideology was measured on an 11-point scale where respondents placed themselves from far left to far right.
Contrary to the researchers’ initial expectations, higher education was not linked to a large jump in outright support for Big Tech. Moving from the lowest to the highest education level increased the predicted probability of being a supporter by only about 3 percentage points, and the probability of being a skeptic by about 2 percentage points. Instead, the probability of belonging to the ambivalent group rose from 22 percent among less educated respondents to 33 percent among university-educated respondents, while the likelihood of being neutral dropped from 43 percent to 30 percent.
Political ideology also separated respondents in distinct ways, with people in the political center most likely to belong to the neutral group. Moving from the center to the far left increased the predicted probability of being a skeptic by about 10 percentage points. Moving from the center to the far right increased the probability of skepticism by about 6 percentage points, while raising the probability of belonging to the ambivalent group by roughly 10 percentage points. These patterns were broadly similar across the six countries, though with some differences.
When the researchers looked at how education and ideology interacted, they found that ideological divisions were sharpest among university-educated citizens, with declining neutrality on the left translating mainly into higher skepticism. On the right, the pattern ran counter to the researchers’ expectations: there was some evidence that support declined toward the far right among the highly educated, while the probability of holding ambivalent views rose by about 16 percentage points from the political center to the far right. The authors suggest this may reflect a conflict between pro-market beliefs and conservative concerns over how tech platforms influence culture and speech.
The authors also examined whether these five attitude groups aligned with policy preferences regarding government regulation and state financial or political backing for tech firms. Across the full sample, 38 percent of respondents favored stronger regulation of Big Tech, 20 percent opposed it, and 42 percent were undecided. Similarly, 32 percent favored giving the companies more economic and political support, 19 percent opposed doing so, and 49 percent remained undecided.
Breaking these numbers down by group showed that attitude profiles closely tracked policy demands. Skeptics overwhelmingly backed stricter regulation at 82 percent and opposed government support for the industry at 65 percent, while supporters showed little appetite for regulation (23 percent in favor) and leaned toward government backing (40 percent in favor). Ambivalent respondents tended to want both interventions simultaneously, with 72 percent favoring more regulation and 46 percent favoring more government support.
These patterns align with research covered by PsyPost earlier this year, which examined public beliefs regarding the economic and labor impacts of artificial intelligence rather than evaluations of Big Tech companies, and similarly found that political ideology structures technology-related attitudes and regulatory preferences. The heightened skepticism on the left is also broadly in line with a 2023 study covered by PsyPost, which analyzed sentiment in news coverage of artificial intelligence rather than public survey attitudes toward major tech corporations and found that liberal-leaning media outlets expressed more negative sentiment toward artificial intelligence than conservative outlets.
To explain why higher education is linked to ambivalence rather than simple support, the authors propose an explanation drawn from a classic theory of how people form political opinions. In this view, education serves as a rough indicator of political awareness, so highly educated people may encounter more competing arguments about both the benefits and dangers of digital platforms. Rather than settling on a one-sided view, they may absorb both sets of arguments, or experience a clash between their economic preferences and cultural values, though the authors note their account remains incomplete.
As with all research, there are some caveats to consider. Because the study relies on survey responses collected at a single point in time in 2022, it cannot establish cause-and-effect relationships or track how attitudes might have shifted following recent breakthroughs in generative artificial intelligence. The survey also included only adults aged 18 to 64 and used quota sampling rather than random sampling, so the results may not fully represent older adults or each country’s population as a whole. In addition, educational attainment overlaps with several other characteristics, such as income and digital literacy, making it difficult to isolate the exact reason why university graduates express more mixed views.
The researchers also note that their analysis treats political messages as broadly similar across the six surveyed nations. In reality, political parties and news media frame technology debates differently across the United States, Japan, and Europe, which could create local variations that broad cross-national models only partly capture. Future studies could track how these public attitudes evolve over time in response to shifting political rhetoric and new regulatory laws.
The study, “Big Tech, big risk? How education and ideology shape public attitudes toward Big Tech companies,” was authored by Tobias Tober, Marius R. Busemeyer, and Sebastian Koos.
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