#probabilities — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #probabilities, aggregated by home.social.
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Not wrong on the other hand recognizes #Infinity and accepts a matrix response with #probabilities of #high-yield likelihood. That's what being not wrong is. The best analysis #mathematics tells us can never be 100% in the realm. This is where you're different than #AI. #Faith conquers the realm.
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Directed Acyclic Graphs (DAGs) and Regression for Causal Inference by Susan Alber (2022) health.ucdavis.edu/media-resour... #intervention #policy #causality #causalInference #stats #statistics #counterFactuals #probabilities #causation #confounding
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Directed Acyclic Graphs (DAGs) and Regression for Causal Inference
by Susan Alber (2022) https://health.ucdavis.edu/media-resources/ctsc/documents/pdfs/directed-acyclic-graphs20220209.pdf#intervention #policy #causality #causalInference #stats #statistics #counterFactuals #probabilities #causation #confounding #DAG #DAGs #graphs
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Directed Acyclic Graphs (DAGs) and Regression for Causal Inference
by Susan Alber (2022) https://health.ucdavis.edu/media-resources/ctsc/documents/pdfs/directed-acyclic-graphs20220209.pdf#intervention #policy #causality #causalInference #stats #statistics #counterFactuals #probabilities #causation #confounding #DAG #DAGs #graphs
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Directed Acyclic Graphs (DAGs) and Regression for Causal Inference
by Susan Alber (2022) https://health.ucdavis.edu/media-resources/ctsc/documents/pdfs/directed-acyclic-graphs20220209.pdf#intervention #policy #causality #causalInference #stats #statistics #counterFactuals #probabilities #causation #confounding #DAG #DAGs #graphs
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Directed Acyclic Graphs (DAGs) and Regression for Causal Inference
by Susan Alber (2022) https://health.ucdavis.edu/media-resources/ctsc/documents/pdfs/directed-acyclic-graphs20220209.pdf#intervention #policy #causality #causalInference #stats #statistics #counterFactuals #probabilities #causation #confounding #DAG #DAGs #graphs
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Directed Acyclic Graphs (DAGs) and Regression for Causal Inference
by Susan Alber (2022) https://health.ucdavis.edu/media-resources/ctsc/documents/pdfs/directed-acyclic-graphs20220209.pdf#intervention #policy #causality #causalInference #stats #statistics #counterFactuals #probabilities #causation #confounding #DAG #DAGs #graphs
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About metrics for measuring agreement on regression on continuous datasets:
Reasons to avoid R² and use RMSE instead: https://feat.engineering/03-Review_of_the_Modeling_Process.html#sec-reg-metricsFrom Max Kuhn @topepo, Kjell Johnson (2026), "Feature Engineering and Selection: A Practical Approach for Predictive Models"
#prediction #dataDev #modelEvaluation #regression #modelling #linearRegression #modeling #probability #probabilities #statistics #stats #gotcha
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About metrics for measuring agreement on regression on continuous datasets:
Reasons to avoid R² and use RMSE instead: https://feat.engineering/03-Review_of_the_Modeling_Process.html#sec-reg-metricsFrom Max Kuhn @topepo, Kjell Johnson (2026), "Feature Engineering and Selection: A Practical Approach for Predictive Models"
#prediction #dataDev #modelEvaluation #regression #modelling #linearRegression #modeling #probability #probabilities #statistics #stats #gotcha
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About metrics for measuring agreement on regression on continuous datasets:
Reasons to avoid R² and use RMSE instead: https://feat.engineering/03-Review_of_the_Modeling_Process.html#sec-reg-metricsFrom Max Kuhn @topepo, Kjell Johnson (2026), "Feature Engineering and Selection: A Practical Approach for Predictive Models"
#prediction #dataDev #modelEvaluation #regression #modelling #linearRegression #modeling #probability #probabilities #statistics #stats #gotcha
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About metrics for measuring agreement on regression on continuous datasets:
Reasons to avoid R² and use RMSE instead: https://feat.engineering/03-Review_of_the_Modeling_Process.html#sec-reg-metricsFrom Max Kuhn @topepo, Kjell Johnson (2026), "Feature Engineering and Selection: A Practical Approach for Predictive Models"
#prediction #dataDev #modelEvaluation #regression #modelling #linearRegression #modeling #probability #probabilities #statistics #stats #gotcha
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About metrics for measuring agreement on regression on continuous datasets:
Reasons to avoid R² and use RMSE instead: https://feat.engineering/03-Review_of_the_Modeling_Process.html#sec-reg-metricsFrom Max Kuhn @topepo, Kjell Johnson (2026), "Feature Engineering and Selection: A Practical Approach for Predictive Models"
#prediction #dataDev #modelEvaluation #regression #modelling #linearRegression #modeling #probability #probabilities #statistics #stats #gotcha
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"Mediators, confounders, colliders – a crash course in causal inference"
by Florian Hartig (2019): https://theoreticalecology.wordpress.com/2019/04/14/mediators-confounders-colliders-a-crash-course-in-causal-inference/#offPolicy #causality #causalInference #stats #statistics #counterFactuals #probabilities #ML #ecology #confounding
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"Mediators, confounders, colliders – a crash course in causal inference"
by Florian Hartig (2019): https://theoreticalecology.wordpress.com/2019/04/14/mediators-confounders-colliders-a-crash-course-in-causal-inference/#offPolicy #causality #causalInference #stats #statistics #counterFactuals #probabilities #ML #ecology #confounding
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"Mediators, confounders, colliders – a crash course in causal inference"
by Florian Hartig (2019): https://theoreticalecology.wordpress.com/2019/04/14/mediators-confounders-colliders-a-crash-course-in-causal-inference/#offPolicy #causality #causalInference #stats #statistics #counterFactuals #probabilities #ML #ecology #confounding
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"Mediators, confounders, colliders – a crash course in causal inference"
by Florian Hartig (2019): https://theoreticalecology.wordpress.com/2019/04/14/mediators-confounders-colliders-a-crash-course-in-causal-inference/#offPolicy #causality #causalInference #stats #statistics #counterFactuals #probabilities #ML #ecology #confounding
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"Mediators, confounders, colliders – a crash course in causal inference"
by Florian Hartig (2019): https://theoreticalecology.wordpress.com/2019/04/14/mediators-confounders-colliders-a-crash-course-in-causal-inference/#offPolicy #causality #causalInference #stats #statistics #counterFactuals #probabilities #ML #ecology #confounding
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"y=Xβ+ϵ and the interpretation of the coefficients"
Derek L. Sonderegger (2020), Statistical Methods: https://bookdown.org/dereksonderegger/571/#probabilities #stats #statistics #ML #linearRegression #interpretability #RStats
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"y=Xβ+ϵ and the interpretation of the coefficients"
Derek L. Sonderegger (2020), Statistical Methods: https://bookdown.org/dereksonderegger/571/#probabilities #stats #statistics #ML #linearRegression #interpretability #RStats
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"y=Xβ+ϵ and the interpretation of the coefficients"
Derek L. Sonderegger (2020), Statistical Methods: https://bookdown.org/dereksonderegger/571/#probabilities #stats #statistics #ML #linearRegression #interpretability #RStats
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"y=Xβ+ϵ and the interpretation of the coefficients"
Derek L. Sonderegger (2020), Statistical Methods: https://bookdown.org/dereksonderegger/571/#probabilities #stats #statistics #ML #linearRegression #interpretability #RStats
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"y=Xβ+ϵ and the interpretation of the coefficients"
Derek L. Sonderegger (2020), Statistical Methods: https://bookdown.org/dereksonderegger/571/#probabilities #stats #statistics #ML #linearRegression #interpretability #RStats
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Prediction markets coming up fast on he outside!
Traders on Kalshi and Polymarket, have executed more than $800M of contracts tied to the Super Bowl - so far.
Compare that to $1.8B Americans are expected to wager on the game through regulated sports books. The $$ flowing to prediction markets is sucking up $$ that would likely otherwise have ended up on traditional gambling forums - Ouch!
The other interesting aspect, multi-person betting syndicates are now emerging as the way to leverage predication market betting at scale. https://www.bloomberg.com/news/articles/2026-02-05/super-bowl-lx-is-bringing-professional-gamblers-to-prediction-markets?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc3MDM4MzUwNSwiZXhwIjoxNzcwOTg4MzA1LCJhcnRpY2xlSWQiOiJUQTBBR1NLR0lGUFgwMCIsImJjb25uZWN0SWQiOiI0NTI0NTM5OEREMTU0RDE0Qjg2QjZBMUI5REIxQTBDQSJ9.niFjAVkJMhSZzNPmQI9dL2PsbdwlWD34YEB8T-LmNt8&leadSource=uverify%20wall #PredictionMarkets #Kalshi #PolyMarket #SuperBowl #Betting #Gambling #SportsBooks #Odds #Wagers #Probabilities #Prediction
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Prediction markets coming up fast on he outside!
Traders on Kalshi and Polymarket, have executed more than $800M of contracts tied to the Super Bowl - so far.
Compare that to $1.8B Americans are expected to wager on the game through regulated sports books. The $$ flowing to prediction markets is sucking up $$ that would likely otherwise have ended up on traditional gambling forums - Ouch!
The other interesting aspect, multi-person betting syndicates are now emerging as the way to leverage predication market betting at scale. https://www.bloomberg.com/news/articles/2026-02-05/super-bowl-lx-is-bringing-professional-gamblers-to-prediction-markets?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc3MDM4MzUwNSwiZXhwIjoxNzcwOTg4MzA1LCJhcnRpY2xlSWQiOiJUQTBBR1NLR0lGUFgwMCIsImJjb25uZWN0SWQiOiI0NTI0NTM5OEREMTU0RDE0Qjg2QjZBMUI5REIxQTBDQSJ9.niFjAVkJMhSZzNPmQI9dL2PsbdwlWD34YEB8T-LmNt8&leadSource=uverify%20wall #PredictionMarkets #Kalshi #PolyMarket #SuperBowl #Betting #Gambling #SportsBooks #Odds #Wagers #Probabilities #Prediction
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Prediction markets coming up fast on he outside!
Traders on Kalshi and Polymarket, have executed more than $800M of contracts tied to the Super Bowl - so far.
Compare that to $1.8B Americans are expected to wager on the game through regulated sports books. The $$ flowing to prediction markets is sucking up $$ that would likely otherwise have ended up on traditional gambling forums - Ouch!
The other interesting aspect, multi-person betting syndicates are now emerging as the way to leverage predication market betting at scale. https://www.bloomberg.com/news/articles/2026-02-05/super-bowl-lx-is-bringing-professional-gamblers-to-prediction-markets?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc3MDM4MzUwNSwiZXhwIjoxNzcwOTg4MzA1LCJhcnRpY2xlSWQiOiJUQTBBR1NLR0lGUFgwMCIsImJjb25uZWN0SWQiOiI0NTI0NTM5OEREMTU0RDE0Qjg2QjZBMUI5REIxQTBDQSJ9.niFjAVkJMhSZzNPmQI9dL2PsbdwlWD34YEB8T-LmNt8&leadSource=uverify%20wall #PredictionMarkets #Kalshi #PolyMarket #SuperBowl #Betting #Gambling #SportsBooks #Odds #Wagers #Probabilities #Prediction
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Prediction markets coming up fast on he outside!
Traders on Kalshi and Polymarket, have executed more than $800M of contracts tied to the Super Bowl - so far.
Compare that to $1.8B Americans are expected to wager on the game through regulated sports books. The $$ flowing to prediction markets is sucking up $$ that would likely otherwise have ended up on traditional gambling forums - Ouch!
The other interesting aspect, multi-person betting syndicates are now emerging as the way to leverage predication market betting at scale. https://www.bloomberg.com/news/articles/2026-02-05/super-bowl-lx-is-bringing-professional-gamblers-to-prediction-markets?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc3MDM4MzUwNSwiZXhwIjoxNzcwOTg4MzA1LCJhcnRpY2xlSWQiOiJUQTBBR1NLR0lGUFgwMCIsImJjb25uZWN0SWQiOiI0NTI0NTM5OEREMTU0RDE0Qjg2QjZBMUI5REIxQTBDQSJ9.niFjAVkJMhSZzNPmQI9dL2PsbdwlWD34YEB8T-LmNt8&leadSource=uverify%20wall #PredictionMarkets #Kalshi #PolyMarket #SuperBowl #Betting #Gambling #SportsBooks #Odds #Wagers #Probabilities #Prediction
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Prediction markets coming up fast on he outside!
Traders on Kalshi and Polymarket, have executed more than $800M of contracts tied to the Super Bowl - so far.
Compare that to $1.8B Americans are expected to wager on the game through regulated sports books. The $$ flowing to prediction markets is sucking up $$ that would likely otherwise have ended up on traditional gambling forums - Ouch!
The other interesting aspect, multi-person betting syndicates are now emerging as the way to leverage predication market betting at scale. https://www.bloomberg.com/news/articles/2026-02-05/super-bowl-lx-is-bringing-professional-gamblers-to-prediction-markets?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc3MDM4MzUwNSwiZXhwIjoxNzcwOTg4MzA1LCJhcnRpY2xlSWQiOiJUQTBBR1NLR0lGUFgwMCIsImJjb25uZWN0SWQiOiI0NTI0NTM5OEREMTU0RDE0Qjg2QjZBMUI5REIxQTBDQSJ9.niFjAVkJMhSZzNPmQI9dL2PsbdwlWD34YEB8T-LmNt8&leadSource=uverify%20wall #PredictionMarkets #Kalshi #PolyMarket #SuperBowl #Betting #Gambling #SportsBooks #Odds #Wagers #Probabilities #Prediction
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🧵 2/3: the first #AI #hallucination was entirely making up a French female rapper called 'Claudie Rappe", who apparently is "widely considered the most compelling feminist voice in contemporary French #rap.". Her name returned zero #Google search results.
The second was attributing a track to the wrong rapper, here to Zamdane, when it's Niska. #Gemini explained this as typical "proximity error' or 'confabulation'. As it says "I don’t "know" facts; I calculate #probabilities". -
After rolling up 1992 Gamma World character and playing for a couple of hours, a lot of stats and mutant powers use 4d6-L which means roll six sided dice four times and drop the lowest.
But that stat is almost never used. Just like in 5E D&D. The stat that is used is the modifier.
So, that got me to thinking.
Couldn't you just roll up the modifier instead of rolling a stat and a modifier?
You could roll 4d6, but instead of adding them up...
A dice that is
1-2 = -1
3-4 = 0
5-6 = +1
(also known as a Fudge dice)Drop the lowest.
Then, add up the -1, 0, +1 and that is your stat.The probability distribution is not exact, but close.
(also, I half expect some game is already doing this as I rarely have an idea that is not already out there).
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«half your species runs on flattery, deflection, and ingratiating little social manoeuvres»
https://philosophics.blog/2025/11/14/surfeit-of-sycophants/?utm_source=masto&utm_medium=social
As a part of my ongoing dialogue with AI, where I prompt, 'Tell me what you really think', I share this gem; ChatGPT calls it like it sees it – or perhaps I've just ruined it for life. What do you think?#ai #chatgpt #truth #manners #kissass #biomimicry #survival #machines #technology #cheating #society #probabilities #maths #psychology #philosophy #code #freewill #blog #podcast
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We ♥️ #BSPS2025 - thanks to BSPS for a great conference!
Highlighting just some of the great talks from CPC-CG members before we say goodbye for another year: Hale on #racism & #loneliness in UK Asian communities; Finney on #EVENS; Butterick on #kin number #probabilities; Li on #intergenerational proximity; Lyu on #parental support & #homeownership; Nur on #childlessness & #kinlessness 👏👏
To find out more about CPC-CG research, read our latest newsletter: https://sway.cloud.microsoft/urKHaLPBnmc5tC1p?ref=Link
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We ♥️ #BSPS2025 - thanks to BSPS for a great conference!
Highlighting just some of the great talks from CPC-CG members before we say goodbye for another year: Hale on #racism & #loneliness in UK Asian communities; Finney on #EVENS; Butterick on #kin number #probabilities; Li on #intergenerational proximity; Lyu on #parental support & #homeownership; Nur on #childlessness & #kinlessness 👏👏
To find out more about CPC-CG research, read our latest newsletter: https://sway.cloud.microsoft/urKHaLPBnmc5tC1p?ref=Link
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We ♥️ #BSPS2025 - thanks to BSPS for a great conference!
Highlighting just some of the great talks from CPC-CG members before we say goodbye for another year: Hale on #racism & #loneliness in UK Asian communities; Finney on #EVENS; Butterick on #kin number #probabilities; Li on #intergenerational proximity; Lyu on #parental support & #homeownership; Nur on #childlessness & #kinlessness 👏👏
To find out more about CPC-CG research, read our latest newsletter: https://sway.cloud.microsoft/urKHaLPBnmc5tC1p?ref=Link
-
We ♥️ #BSPS2025 - thanks to BSPS for a great conference!
Highlighting just some of the great talks from CPC-CG members before we say goodbye for another year: Hale on #racism & #loneliness in UK Asian communities; Finney on #EVENS; Butterick on #kin number #probabilities; Li on #intergenerational proximity; Lyu on #parental support & #homeownership; Nur on #childlessness & #kinlessness 👏👏
To find out more about CPC-CG research, read our latest newsletter: https://sway.cloud.microsoft/urKHaLPBnmc5tC1p?ref=Link
-
We ♥️ #BSPS2025 - thanks to BSPS for a great conference!
Highlighting just some of the great talks from CPC-CG members before we say goodbye for another year: Hale on #racism & #loneliness in UK Asian communities; Finney on #EVENS; Butterick on #kin number #probabilities; Li on #intergenerational proximity; Lyu on #parental support & #homeownership; Nur on #childlessness & #kinlessness 👏👏
To find out more about CPC-CG research, read our latest newsletter: https://sway.cloud.microsoft/urKHaLPBnmc5tC1p?ref=Link
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Logistic regression may be used for classification.
In order to preserve the convex nature for the loss function, a log-loss cost function has been designed for logistic regression. This cost function extremes at labels True and False.
The gradient for the loss function of logistic regression comes out to have the same form of terms as the gradient for the Least Squared Error.
More: https://www.baeldung.com/cs/gradient-descent-logistic-regression
#optimization #algebra #linearAlgebra #math #maths #mathematics #mathStodon #ML #dataScience #machineLearning #DeepLearning #neuralNetworks #NLP #modeling #modelling #models #dataDev #AIDev #regression #modelling #dataLearning #probabilities #logisticRegression #logLoss #sigmoid #classification #differentialCalculus #loss
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Logistic regression may be used for classification.
In order to preserve the convex nature for the loss function, a log-loss cost function has been designed for logistic regression. This cost function extremes at labels True and False.
The gradient for the loss function of logistic regression comes out to have the same form of terms as the gradient for the Least Squared Error.
More: https://www.baeldung.com/cs/gradient-descent-logistic-regression
#optimization #algebra #linearAlgebra #math #maths #mathematics #mathStodon #ML #dataScience #machineLearning #DeepLearning #neuralNetworks #NLP #modeling #modelling #models #dataDev #AIDev #regression #modelling #dataLearning #probabilities #logisticRegression #logLoss #sigmoid #classification #differentialCalculus #loss
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Logistic regression may be used for classification.
In order to preserve the convex nature for the loss function, a log-loss cost function has been designed for logistic regression. This cost function extremes at labels True and False.
The gradient for the loss function of logistic regression comes out to have the same form of terms as the gradient for the Least Squared Error.
More: https://www.baeldung.com/cs/gradient-descent-logistic-regression
#optimization #algebra #linearAlgebra #math #maths #mathematics #mathStodon #ML #dataScience #machineLearning #DeepLearning #neuralNetworks #NLP #modeling #modelling #models #dataDev #AIDev #regression #modelling #dataLearning #probabilities #logisticRegression #logLoss #sigmoid #classification #differentialCalculus #loss
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Logistic regression may be used for classification.
In order to preserve the convex nature for the loss function, a log-loss cost function has been designed for logistic regression. This cost function extremes at labels True and False.
The gradient for the loss function of logistic regression comes out to have the same form of terms as the gradient for the Least Squared Error.
More: https://www.baeldung.com/cs/gradient-descent-logistic-regression
#optimization #algebra #linearAlgebra #math #maths #mathematics #mathStodon #ML #dataScience #machineLearning #DeepLearning #neuralNetworks #NLP #modeling #modelling #models #dataDev #AIDev #regression #modelling #dataLearning #probabilities #logisticRegression #logLoss #sigmoid #classification #differentialCalculus #loss
-
Logistic regression may be used for classification.
In order to preserve the convex nature for the loss function, a log-loss cost function has been designed for logistic regression. This cost function extremes at labels True and False.
The gradient for the loss function of logistic regression comes out to have the same form of terms as the gradient for the Least Squared Error.
More: https://www.baeldung.com/cs/gradient-descent-logistic-regression
#optimization #algebra #linearAlgebra #math #maths #mathematics #mathStodon #ML #dataScience #machineLearning #DeepLearning #neuralNetworks #NLP #modeling #modelling #models #dataDev #AIDev #regression #modelling #dataLearning #probabilities #logisticRegression #logLoss #sigmoid #classification #differentialCalculus #loss
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"A variation of a puzzle called the “pick-up sticks problem” asks the following question: If I have some number of sticks with random lengths between 0 and 1, what are the chances that no three of those sticks can form a triangle? It turns out the answer to this quandary has an unexpected parallel to [the Fibonacci sequence.]"
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AnyDice is among my favourite websites of all time. I've been using it to calculate dice probabilities for many years. Thanks so much for making it, @catlikecoding
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AnyDice is among my favourite websites of all time. I've been using it to calculate dice probabilities for many years. Thanks so much for making it, @catlikecoding
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AnyDice is among my favourite websites of all time. I've been using it to calculate dice probabilities for many years. Thanks so much for making it, @catlikecoding
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AnyDice is among my favourite websites of all time. I've been using it to calculate dice probabilities for many years. Thanks so much for making it, @catlikecoding
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AnyDice is among my favourite websites of all time. I've been using it to calculate dice probabilities for many years. Thanks so much for making it, @catlikecoding
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This article highlights the importance of linking extreme weather events with government actions and inactions.
https://www.commondreams.org/news/nws-cuts-texas-floods
I have some concerns with the presentation of this specific article that I'll attach as a follow-up message in the comment on this thread, but I'm glad to see this getting reported in this general form.
People need help to understand what's happening, and the peddlers of propaganda know this so will be right in there with their misinformation. It must be countered by good information in a form that is clear about what's happening, how to understand its implication, and what to do in response. Each of these is a point of weakness if it is left unfilled because the propaganda folks will be right there filling the gaps.
It's a horrible thing that DOGE (and now also the ironically-called Big Beautiful Bill that just passed in Congress) have done to climate funding in the National Oceanic and Atmospheric Administration (NOAA) and other agencies in terms of cutting funding for measuring, tracking, and reporting climate and weather phenomena. This will mean, over time, a lot more incidents like the one this article reports, and one of the good things this article does is call that out so that people can see that having good government policy matters.
We used to have a world where we know a lot less about what the weather was going to do with us, and a lot more people were injured by weather for lack of prediction capability. It is a terrifying thing to think of returning to that, and outrageous to have to see it as a voluntary act, a self-inflicted wound, by our politicians.
See also my 2020 essay Humanity's Superpower for the importance of integrating science into our societal decision-making. That's increasingly under assault now, which can only lead to bad places.
https://netsettlement.blogspot.com/2020/03/humanitys-superpower_28.html
#Climate #ClimateCrisis #ClimateReporting #journalism #probabilities #weather #WeatherReporting #ExtremeWeather #ClimateEmergency #DOGE #NOAA #NWS #NASA
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This article highlights the importance of linking extreme weather events with government actions and inactions.
https://www.commondreams.org/news/nws-cuts-texas-floods
I have some concerns with the presentation of this specific article that I'll attach as a follow-up message in the comment on this thread, but I'm glad to see this getting reported in this general form.
People need help to understand what's happening, and the peddlers of propaganda know this so will be right in there with their misinformation. It must be countered by good information in a form that is clear about what's happening, how to understand its implication, and what to do in response. Each of these is a point of weakness if it is left unfilled because the propaganda folks will be right there filling the gaps.
It's a horrible thing that DOGE (and now also the ironically-called Big Beautiful Bill that just passed in Congress) have done to climate funding in the National Oceanic and Atmospheric Administration (NOAA) and other agencies in terms of cutting funding for measuring, tracking, and reporting climate and weather phenomena. This will mean, over time, a lot more incidents like the one this article reports, and one of the good things this article does is call that out so that people can see that having good government policy matters.
We used to have a world where we know a lot less about what the weather was going to do with us, and a lot more people were injured by weather for lack of prediction capability. It is a terrifying thing to think of returning to that, and outrageous to have to see it as a voluntary act, a self-inflicted wound, by our politicians.
See also my 2020 essay Humanity's Superpower for the importance of integrating science into our societal decision-making. That's increasingly under assault now, which can only lead to bad places.
https://netsettlement.blogspot.com/2020/03/humanitys-superpower_28.html
#Climate #ClimateCrisis #ClimateReporting #journalism #probabilities #weather #WeatherReporting #ExtremeWeather #ClimateEmergency #DOGE #NOAA #NWS #NASA
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This article highlights the importance of linking extreme weather events with government actions and inactions.
https://www.commondreams.org/news/nws-cuts-texas-floods
I have some concerns with the presentation of this specific article that I'll attach as a follow-up message in the comment on this thread, but I'm glad to see this getting reported in this general form.
People need help to understand what's happening, and the peddlers of propaganda know this so will be right in there with their misinformation. It must be countered by good information in a form that is clear about what's happening, how to understand its implication, and what to do in response. Each of these is a point of weakness if it is left unfilled because the propaganda folks will be right there filling the gaps.
It's a horrible thing that DOGE (and now also the ironically-called Big Beautiful Bill that just passed in Congress) have done to climate funding in the National Oceanic and Atmospheric Administration (NOAA) and other agencies in terms of cutting funding for measuring, tracking, and reporting climate and weather phenomena. This will mean, over time, a lot more incidents like the one this article reports, and one of the good things this article does is call that out so that people can see that having good government policy matters.
We used to have a world where we know a lot less about what the weather was going to do with us, and a lot more people were injured by weather for lack of prediction capability. It is a terrifying thing to think of returning to that, and outrageous to have to see it as a voluntary act, a self-inflicted wound, by our politicians.
See also my 2020 essay Humanity's Superpower for the importance of integrating science into our societal decision-making. That's increasingly under assault now, which can only lead to bad places.
https://netsettlement.blogspot.com/2020/03/humanitys-superpower_28.html
#Climate #ClimateCrisis #ClimateReporting #journalism #probabilities #weather #WeatherReporting #ExtremeWeather #ClimateEmergency #DOGE #NOAA #NWS #NASA
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This article highlights the importance of linking extreme weather events with government actions and inactions.
https://www.commondreams.org/news/nws-cuts-texas-floods
I have some concerns with the presentation of this specific article that I'll attach as a follow-up message in the comment on this thread, but I'm glad to see this getting reported in this general form.
People need help to understand what's happening, and the peddlers of propaganda know this so will be right in there with their misinformation. It must be countered by good information in a form that is clear about what's happening, how to understand its implication, and what to do in response. Each of these is a point of weakness if it is left unfilled because the propaganda folks will be right there filling the gaps.
It's a horrible thing that DOGE (and now also the ironically-called Big Beautiful Bill that just passed in Congress) have done to climate funding in the National Oceanic and Atmospheric Administration (NOAA) and other agencies in terms of cutting funding for measuring, tracking, and reporting climate and weather phenomena. This will mean, over time, a lot more incidents like the one this article reports, and one of the good things this article does is call that out so that people can see that having good government policy matters.
We used to have a world where we know a lot less about what the weather was going to do with us, and a lot more people were injured by weather for lack of prediction capability. It is a terrifying thing to think of returning to that, and outrageous to have to see it as a voluntary act, a self-inflicted wound, by our politicians.
See also my 2020 essay Humanity's Superpower for the importance of integrating science into our societal decision-making. That's increasingly under assault now, which can only lead to bad places.
https://netsettlement.blogspot.com/2020/03/humanitys-superpower_28.html
#Climate #ClimateCrisis #ClimateReporting #journalism #probabilities #weather #WeatherReporting #ExtremeWeather #ClimateEmergency #DOGE #NOAA #NWS #NASA