#categorization — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #categorization, aggregated by home.social.
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New regulations passed by the European Parliament in Strasbourg stipulate that the genetic characteristics of crops, rather than their breeding method, will det... https://news.osna.fm/?p=51437 | #news #allows #categorization #crops #dnamodified
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New regulations passed by the European Parliament in Strasbourg stipulate that the genetic characteristics of crops, rather than their breeding method, will det... https://news.osna.fm/?p=51437 | #news #allows #categorization #crops #dnamodified
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New regulations passed by the European Parliament in Strasbourg stipulate that the genetic characteristics of crops, rather than their breeding method, will det... https://news.osna.fm/?p=51437 | #news #allows #categorization #crops #dnamodified
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The Box You Cannot Check
The clinic intake form on the clipboard at the front desk has two boxes next to the word “sex.” A patient who is neither of the two options has been given three choices: pick one box and lie, write something in the margin, or refuse the form. The receptionist will not read the margin. Data entry clerks will not transcribe it. EHR systems will not store anything outside the two values the form lists. The patient walks out of the clinic with a treatment plan based on a box that does not correspond to their body, their history, or their current endocrine state. The form has done its job, which is not the job it claimed to do.
The form claims to collect information. Its actual function is categorization. Information collection would mean recording what the patient told the clinic. Categorization means sorting the patient into one of the boxes the system already had, regardless of whether the patient fits. These are different operations. The form does the second while presenting itself as doing the first.
I focus on the sex/gender field because it is currently the most visible example of the categorization failure, but the pattern is general. Race fields on most forms still offer five or six options plus an “other” line that researchers routinely discard in aggregate analysis because “other” cannot be merged with the named categories without distorting the comparison the categories were built to support. Ethnicity fields on US forms famously split Hispanic into its own question while leaving Middle Eastern and North African respondents to choose between “White,” “Asian,” and “Other,” none of which describes them. The Census Bureau plans to add a MENA category in 2030, decades after the gap was identified. Respondents could check multiple race boxes for the first time in 2000, which was a real improvement on prior forms. The same census kept the sex question as a binary male/female, the way every US Census has since 1790, on the grounds that adding a third option would compromise the time series.
The time series argument is worth examining because it surfaces what is actually happening. A research instrument that has measured a binary for 230 years has produced 230 years of data that reads the population as binary. Adding a third or fourth or fifth option in 2030 would mean that comparisons between 2020 and 2030 require methodological accommodation. That accommodation is doable, well-documented in survey methodology, and routine when other categories shift. Choosing not to make the accommodation keeps the data legible to historians of a category system that is no longer the category system in use. The form preserves the past at the cost of misrepresenting the present.
What happens to the data after the form is the harder problem. A survey of 10,000 people that includes 9,200 binary-box-checkers, 600 “other” or write-in responses, and 200 refusals will, in most aggregate reports, appear as a clean 9,200-person dataset. The 600 “other” responses get coded as missing, recoded into the binary categories by an analyst making a judgment call, or dropped entirely under a methodology footnote that says “respondents who declined to specify were excluded from analysis.” Another 200 refusals disappear under one of those clauses. A final published table reads as if 9,200 people answered the question cleanly, when in fact 10,000 people interacted with the question and 800 of them produced data the analyst could not use.
The aggregate therefore summarizes only the inputs that fit the categories already chosen. This is the gap between what the form does and what the form claims to do. The form does classification work while presenting itself as a question. Its classification system was built before the form was printed, and respondents who do not fit that classification are removed from the dataset the form generates. The dataset reads as comprehensive because the cleaning happened before anyone with access to the aggregate could see what was removed.
The mathematical consequence of this should bother statisticians more than it currently does. A dataset that excludes 8 percent of respondents on the grounds that their responses were illegible has an 8 percent selection bias that propagates into every downstream analysis. Confidence intervals computed on the 9,200 do not account for the 800. P-values look strong because the variance in the included data is smaller than the variance in the actual respondent pool. Models trained on the cleaned data fit the cleaned data well and fail in production when they encounter the kind of respondent the cleaning removed. Every machine learning system that classifies people on the basis of survey-derived training data carries this bias forward in ways the system’s documentation almost never describes.
The political consequence is what I think interests the new readers who arrived after the elevator essay. A form that excludes a category of people from the dataset also excludes that category from the policy decisions the dataset informs. A health system that does not record nonbinary patients in a way its analytics engine can read does not know how many nonbinary patients it serves, does not allocate resources to nonbinary patient care, does not train staff to address nonbinary patient needs, and does not appear in funding requests for nonbinary patient programs because the funding agency requires headcount data the EHR cannot produce. The form is upstream of the spreadsheet, the spreadsheet upstream of the budget, the budget upstream of the clinic. By the time the missing patients show up at the front desk, the building has been designed for the patients the form was capable of recording.
A clinic that fixes its form does not solve the problem because the EHR vendor downstream still has a two-value field. Fixing the EHR fails because the state public health reporting system still requires data in the older format. Fixing the state system fails because the federal CDC reporting standard underneath still uses the binary. The categorization is layered. Each layer has a defensible local reason for the binary it inherited. The cumulative effect is a healthcare system that cannot count its actual patient population, and a healthcare system that cannot count cannot fund, and a healthcare system that cannot fund cannot serve. The form on the clipboard at the front desk is the bottom button of a fifteen-story panel where every button on every floor is wired to the same controller, and the controller only stops the elevator on floors the original engineer drew on the original blueprint.
The fix has the same structure as the placebo button fix. Recognize which boxes work and which do not. Refuse to mistake compliance for collection. Push for upstream rewiring of forms before adding more “other” lines downstream. Demand that aggregate reports publish the count of excluded responses in the same table as the included ones, with the same prominence, in the same font. Refuse to treat a survey that loses 8 percent of its respondents as a survey of the population it sampled. Insist on the difference between a question that asks and a question that classifies, and refuse to fill out the second one as if it were the first.
The form is not neutral. It encodes what its designers were willing to recognize, and it discards what its designers were not willing to recognize, and the discard happens silently in the data pipeline rather than visibly at the front desk. A patient who writes a third answer in the margin is doing the work the form refused to do. An aggregate report that publishes 9,200 clean responses hides 800 acts of refusal by people who would not lie to the clipboard. Counting is the claim. Selection is the politics. That politics rides downstream into every room the dataset enters, every dollar the budget allocates, every protocol the staff is trained on, and every body the building was built to serve.
#binary #categorization #category #education #ehrSystems #ethnicity #female #gender #human #male #medicine #MENA #nonbinary #race #sex #tech #timeSeries -
The Box You Cannot Check
The clinic intake form on the clipboard at the front desk has two boxes next to the word “sex.” A patient who is neither of the two options has been given three choices: pick one box and lie, write something in the margin, or refuse the form. The receptionist will not read the margin. Data entry clerks will not transcribe it. EHR systems will not store anything outside the two values the form lists. The patient walks out of the clinic with a treatment plan based on a box that does not correspond to their body, their history, or their current endocrine state. The form has done its job, which is not the job it claimed to do.
The form claims to collect information. Its actual function is categorization. Information collection would mean recording what the patient told the clinic. Categorization means sorting the patient into one of the boxes the system already had, regardless of whether the patient fits. These are different operations. The form does the second while presenting itself as doing the first.
I focus on the sex/gender field because it is currently the most visible example of the categorization failure, but the pattern is general. Race fields on most forms still offer five or six options plus an “other” line that researchers routinely discard in aggregate analysis because “other” cannot be merged with the named categories without distorting the comparison the categories were built to support. Ethnicity fields on US forms famously split Hispanic into its own question while leaving Middle Eastern and North African respondents to choose between “White,” “Asian,” and “Other,” none of which describes them. The Census Bureau plans to add a MENA category in 2030, decades after the gap was identified. Respondents could check multiple race boxes for the first time in 2000, which was a real improvement on prior forms. The same census kept the sex question as a binary male/female, the way every US Census has since 1790, on the grounds that adding a third option would compromise the time series.
The time series argument is worth examining because it surfaces what is actually happening. A research instrument that has measured a binary for 230 years has produced 230 years of data that reads the population as binary. Adding a third or fourth or fifth option in 2030 would mean that comparisons between 2020 and 2030 require methodological accommodation. That accommodation is doable, well-documented in survey methodology, and routine when other categories shift. Choosing not to make the accommodation keeps the data legible to historians of a category system that is no longer the category system in use. The form preserves the past at the cost of misrepresenting the present.
What happens to the data after the form is the harder problem. A survey of 10,000 people that includes 9,200 binary-box-checkers, 600 “other” or write-in responses, and 200 refusals will, in most aggregate reports, appear as a clean 9,200-person dataset. The 600 “other” responses get coded as missing, recoded into the binary categories by an analyst making a judgment call, or dropped entirely under a methodology footnote that says “respondents who declined to specify were excluded from analysis.” Another 200 refusals disappear under one of those clauses. A final published table reads as if 9,200 people answered the question cleanly, when in fact 10,000 people interacted with the question and 800 of them produced data the analyst could not use.
The aggregate therefore summarizes only the inputs that fit the categories already chosen. This is the gap between what the form does and what the form claims to do. The form does classification work while presenting itself as a question. Its classification system was built before the form was printed, and respondents who do not fit that classification are removed from the dataset the form generates. The dataset reads as comprehensive because the cleaning happened before anyone with access to the aggregate could see what was removed.
The mathematical consequence of this should bother statisticians more than it currently does. A dataset that excludes 8 percent of respondents on the grounds that their responses were illegible has an 8 percent selection bias that propagates into every downstream analysis. Confidence intervals computed on the 9,200 do not account for the 800. P-values look strong because the variance in the included data is smaller than the variance in the actual respondent pool. Models trained on the cleaned data fit the cleaned data well and fail in production when they encounter the kind of respondent the cleaning removed. Every machine learning system that classifies people on the basis of survey-derived training data carries this bias forward in ways the system’s documentation almost never describes.
The political consequence is what I think interests the new readers who arrived after the elevator essay. A form that excludes a category of people from the dataset also excludes that category from the policy decisions the dataset informs. A health system that does not record nonbinary patients in a way its analytics engine can read does not know how many nonbinary patients it serves, does not allocate resources to nonbinary patient care, does not train staff to address nonbinary patient needs, and does not appear in funding requests for nonbinary patient programs because the funding agency requires headcount data the EHR cannot produce. The form is upstream of the spreadsheet, the spreadsheet upstream of the budget, the budget upstream of the clinic. By the time the missing patients show up at the front desk, the building has been designed for the patients the form was capable of recording.
A clinic that fixes its form does not solve the problem because the EHR vendor downstream still has a two-value field. Fixing the EHR fails because the state public health reporting system still requires data in the older format. Fixing the state system fails because the federal CDC reporting standard underneath still uses the binary. The categorization is layered. Each layer has a defensible local reason for the binary it inherited. The cumulative effect is a healthcare system that cannot count its actual patient population, and a healthcare system that cannot count cannot fund, and a healthcare system that cannot fund cannot serve. The form on the clipboard at the front desk is the bottom button of a fifteen-story panel where every button on every floor is wired to the same controller, and the controller only stops the elevator on floors the original engineer drew on the original blueprint.
The fix has the same structure as the placebo button fix. Recognize which boxes work and which do not. Refuse to mistake compliance for collection. Push for upstream rewiring of forms before adding more “other” lines downstream. Demand that aggregate reports publish the count of excluded responses in the same table as the included ones, with the same prominence, in the same font. Refuse to treat a survey that loses 8 percent of its respondents as a survey of the population it sampled. Insist on the difference between a question that asks and a question that classifies, and refuse to fill out the second one as if it were the first.
The form is not neutral. It encodes what its designers were willing to recognize, and it discards what its designers were not willing to recognize, and the discard happens silently in the data pipeline rather than visibly at the front desk. A patient who writes a third answer in the margin is doing the work the form refused to do. An aggregate report that publishes 9,200 clean responses hides 800 acts of refusal by people who would not lie to the clipboard. Counting is the claim. Selection is the politics. That politics rides downstream into every room the dataset enters, every dollar the budget allocates, every protocol the staff is trained on, and every body the building was built to serve.
#binary #categorization #category #education #ehrSystems #ethnicity #female #gender #human #male #medicine #MENA #nonbinary #race #sex #tech #timeSeries -
The Box You Cannot Check
The clinic intake form on the clipboard at the front desk has two boxes next to the word “sex.” A patient who is neither of the two options has been given three choices: pick one box and lie, write something in the margin, or refuse the form. The receptionist will not read the margin. Data entry clerks will not transcribe it. EHR systems will not store anything outside the two values the form lists. The patient walks out of the clinic with a treatment plan based on a box that does not correspond to their body, their history, or their current endocrine state. The form has done its job, which is not the job it claimed to do.
The form claims to collect information. Its actual function is categorization. Information collection would mean recording what the patient told the clinic. Categorization means sorting the patient into one of the boxes the system already had, regardless of whether the patient fits. These are different operations. The form does the second while presenting itself as doing the first.
I focus on the sex/gender field because it is currently the most visible example of the categorization failure, but the pattern is general. Race fields on most forms still offer five or six options plus an “other” line that researchers routinely discard in aggregate analysis because “other” cannot be merged with the named categories without distorting the comparison the categories were built to support. Ethnicity fields on US forms famously split Hispanic into its own question while leaving Middle Eastern and North African respondents to choose between “White,” “Asian,” and “Other,” none of which describes them. The Census Bureau plans to add a MENA category in 2030, decades after the gap was identified. Respondents could check multiple race boxes for the first time in 2000, which was a real improvement on prior forms. The same census kept the sex question as a binary male/female, the way every US Census has since 1790, on the grounds that adding a third option would compromise the time series.
The time series argument is worth examining because it surfaces what is actually happening. A research instrument that has measured a binary for 230 years has produced 230 years of data that reads the population as binary. Adding a third or fourth or fifth option in 2030 would mean that comparisons between 2020 and 2030 require methodological accommodation. That accommodation is doable, well-documented in survey methodology, and routine when other categories shift. Choosing not to make the accommodation keeps the data legible to historians of a category system that is no longer the category system in use. The form preserves the past at the cost of misrepresenting the present.
What happens to the data after the form is the harder problem. A survey of 10,000 people that includes 9,200 binary-box-checkers, 600 “other” or write-in responses, and 200 refusals will, in most aggregate reports, appear as a clean 9,200-person dataset. The 600 “other” responses get coded as missing, recoded into the binary categories by an analyst making a judgment call, or dropped entirely under a methodology footnote that says “respondents who declined to specify were excluded from analysis.” Another 200 refusals disappear under one of those clauses. A final published table reads as if 9,200 people answered the question cleanly, when in fact 10,000 people interacted with the question and 800 of them produced data the analyst could not use.
The aggregate therefore summarizes only the inputs that fit the categories already chosen. This is the gap between what the form does and what the form claims to do. The form does classification work while presenting itself as a question. Its classification system was built before the form was printed, and respondents who do not fit that classification are removed from the dataset the form generates. The dataset reads as comprehensive because the cleaning happened before anyone with access to the aggregate could see what was removed.
The mathematical consequence of this should bother statisticians more than it currently does. A dataset that excludes 8 percent of respondents on the grounds that their responses were illegible has an 8 percent selection bias that propagates into every downstream analysis. Confidence intervals computed on the 9,200 do not account for the 800. P-values look strong because the variance in the included data is smaller than the variance in the actual respondent pool. Models trained on the cleaned data fit the cleaned data well and fail in production when they encounter the kind of respondent the cleaning removed. Every machine learning system that classifies people on the basis of survey-derived training data carries this bias forward in ways the system’s documentation almost never describes.
The political consequence is what I think interests the new readers who arrived after the elevator essay. A form that excludes a category of people from the dataset also excludes that category from the policy decisions the dataset informs. A health system that does not record nonbinary patients in a way its analytics engine can read does not know how many nonbinary patients it serves, does not allocate resources to nonbinary patient care, does not train staff to address nonbinary patient needs, and does not appear in funding requests for nonbinary patient programs because the funding agency requires headcount data the EHR cannot produce. The form is upstream of the spreadsheet, the spreadsheet upstream of the budget, the budget upstream of the clinic. By the time the missing patients show up at the front desk, the building has been designed for the patients the form was capable of recording.
A clinic that fixes its form does not solve the problem because the EHR vendor downstream still has a two-value field. Fixing the EHR fails because the state public health reporting system still requires data in the older format. Fixing the state system fails because the federal CDC reporting standard underneath still uses the binary. The categorization is layered. Each layer has a defensible local reason for the binary it inherited. The cumulative effect is a healthcare system that cannot count its actual patient population, and a healthcare system that cannot count cannot fund, and a healthcare system that cannot fund cannot serve. The form on the clipboard at the front desk is the bottom button of a fifteen-story panel where every button on every floor is wired to the same controller, and the controller only stops the elevator on floors the original engineer drew on the original blueprint.
The fix has the same structure as the placebo button fix. Recognize which boxes work and which do not. Refuse to mistake compliance for collection. Push for upstream rewiring of forms before adding more “other” lines downstream. Demand that aggregate reports publish the count of excluded responses in the same table as the included ones, with the same prominence, in the same font. Refuse to treat a survey that loses 8 percent of its respondents as a survey of the population it sampled. Insist on the difference between a question that asks and a question that classifies, and refuse to fill out the second one as if it were the first.
The form is not neutral. It encodes what its designers were willing to recognize, and it discards what its designers were not willing to recognize, and the discard happens silently in the data pipeline rather than visibly at the front desk. A patient who writes a third answer in the margin is doing the work the form refused to do. An aggregate report that publishes 9,200 clean responses hides 800 acts of refusal by people who would not lie to the clipboard. Counting is the claim. Selection is the politics. That politics rides downstream into every room the dataset enters, every dollar the budget allocates, every protocol the staff is trained on, and every body the building was built to serve.
#binary #categorization #category #education #ehrSystems #ethnicity #female #gender #human #male #medicine #MENA #nonbinary #race #sex #tech #timeSeries -
Shit you see in the physical therapist's office: a handy copy of the Bristol Stool Form Scale
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Shit you see in the physical therapist's office: a handy copy of the Bristol Stool Form Scale
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Shit you see in the physical therapist's office: a handy copy of the Bristol Stool Form Scale
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Shit you see in the physical therapist's office: a handy copy of the Bristol Stool Form Scale
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Shit you see in the physical therapist's office: a handy copy of the Bristol Stool Form Scale
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A quotation from Nassim Nicholas Taleb
Categorizing is necessary for humans, but it becomes pathological when the category is seen as definitive, preventing people from considering the fuzziness of boundaries, let alone revising their categories.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist
The Black Swan, Part 1, ch. 1 “The Apprenticeship of an Empirical Skeptic” (2007)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #qotd #reality #truth #boundaries #brightline #categorization #category #classification #complexity #comprehension #inflexibility
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A quotation from Nassim Nicholas Taleb
Categorizing is necessary for humans, but it becomes pathological when the category is seen as definitive, preventing people from considering the fuzziness of boundaries, let alone revising their categories.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist
The Black Swan, Part 1, ch. 1 “The Apprenticeship of an Empirical Skeptic” (2007)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #qotd #reality #truth #boundaries #brightline #categorization #category #classification #complexity #comprehension #inflexibility
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A quotation from Nassim Nicholas Taleb
Categorizing is necessary for humans, but it becomes pathological when the category is seen as definitive, preventing people from considering the fuzziness of boundaries, let alone revising their categories.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist
The Black Swan, Part 1, ch. 1 “The Apprenticeship of an Empirical Skeptic” (2007)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #qotd #reality #truth #boundaries #brightline #categorization #category #classification #complexity #comprehension #inflexibility
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A quotation from Nassim Nicholas Taleb
Categorizing is necessary for humans, but it becomes pathological when the category is seen as definitive, preventing people from considering the fuzziness of boundaries, let alone revising their categories.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist
The Black Swan, Part 1, ch. 1 “The Apprenticeship of an Empirical Skeptic” (2007)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #qotd #reality #truth #boundaries #brightline #categorization #category #classification #complexity #comprehension #inflexibility
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A quotation from Ambrose Bierce
PHYSIOGNOMY, n. The art of determining the character of another by the resemblances and differences between his face and our own, which is the standard of excellence.
Ambrose Bierce (1842-1914?) American writer and journalist
“Physiognomy,” The Devil’s Dictionary (1911)Sourcing, notes: wist.info/bierce-ambrose/75545…
#quote #quotes #quotation #appearance #bias #categorization #character #ego #norm #phrenology #physiognomy #prejudice #standard
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A quotation from Ambrose Bierce
PHYSIOGNOMY, n. The art of determining the character of another by the resemblances and differences between his face and our own, which is the standard of excellence.
Ambrose Bierce (1842-1914?) American writer and journalist
“Physiognomy,” The Devil’s Dictionary (1911)Sourcing, notes: wist.info/bierce-ambrose/75545…
#quote #quotes #quotation #appearance #bias #categorization #character #ego #norm #phrenology #physiognomy #prejudice #standard
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A quotation from Ambrose Bierce
PHYSIOGNOMY, n. The art of determining the character of another by the resemblances and differences between his face and our own, which is the standard of excellence.
Ambrose Bierce (1842-1914?) American writer and journalist
“Physiognomy,” The Devil’s Dictionary (1911)Sourcing, notes: wist.info/bierce-ambrose/75545…
#quote #quotes #quotation #appearance #bias #categorization #character #ego #norm #phrenology #physiognomy #prejudice #standard
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A quotation from Robert Benchley
There may be said to be two classes of people in the world: those who constantly divide the people of the world into two classes, and those who do not.
Robert Benchley (1889-1945) American humorist, columnist, actor, wit
Of All Things, ch. 20 “The Most Popular Book of the Month” (1921)Sourcing, notes: wist.info/benchley-robert/7523…
#quote #quotes #quotation #categorization #classification #division #generalities #humanity #people #types
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A quotation from Robert Benchley
There may be said to be two classes of people in the world: those who constantly divide the people of the world into two classes, and those who do not.
Robert Benchley (1889-1945) American humorist, columnist, actor, wit
Of All Things, ch. 20 “The Most Popular Book of the Month” (1921)Sourcing, notes: wist.info/benchley-robert/7523…
#quote #quotes #quotation #categorization #classification #division #generalities #humanity #people #types
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A quotation from Robert Benchley
There may be said to be two classes of people in the world: those who constantly divide the people of the world into two classes, and those who do not.
Robert Benchley (1889-1945) American humorist, columnist, actor, wit
Of All Things, ch. 20 “The Most Popular Book of the Month” (1921)Sourcing, notes: wist.info/benchley-robert/7523…
#quote #quotes #quotation #categorization #classification #division #generalities #humanity #people #types
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A quotation from Robert Benchley
There may be said to be two classes of people in the world: those who constantly divide the people of the world into two classes, and those who do not.
Robert Benchley (1889-1945) American humorist, columnist, actor, wit
Of All Things, ch. 20 “The Most Popular Book of the Month” (1921)Sourcing, notes: wist.info/benchley-robert/7523…
#quote #quotes #quotation #categorization #classification #division #generalities #humanity #people #types
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A quotation from Robert Benchley
There may be said to be two classes of people in the world: those who constantly divide the people of the world into two classes, and those who do not.
Robert Benchley (1889-1945) American humorist, columnist, actor, wit
Of All Things, ch. 20 “The Most Popular Book of the Month” (1921)Sourcing, notes: wist.info/benchley-robert/7523…
#quote #quotes #quotation #categorization #classification #division #generalities #humanity #people #types
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A quotation from Nicholas Taleb
We humans, facing limits of knowledge, and things we do not observe, the unseen and the unknown, resolve the tension by squeezing life and the world into crisp commoditized ideas, reductive categories, specific vocabularies, and prepackaged narratives, which, on the occasion, has explosive consequences.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist.
The Bed of Procrustes: Philosophical and Practical Aphorisms, Introduction (2010)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #categories #categorization #knowledge #mind #narratives #oversimplification #patterns #shortcut #simplicity #tropes #understanding
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A quotation from Nicholas Taleb
We humans, facing limits of knowledge, and things we do not observe, the unseen and the unknown, resolve the tension by squeezing life and the world into crisp commoditized ideas, reductive categories, specific vocabularies, and prepackaged narratives, which, on the occasion, has explosive consequences.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist.
The Bed of Procrustes: Philosophical and Practical Aphorisms, Introduction (2010)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #categories #categorization #knowledge #mind #narratives #oversimplification #patterns #shortcut #simplicity #tropes #understanding
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A quotation from Nicholas Taleb
We humans, facing limits of knowledge, and things we do not observe, the unseen and the unknown, resolve the tension by squeezing life and the world into crisp commoditized ideas, reductive categories, specific vocabularies, and prepackaged narratives, which, on the occasion, has explosive consequences.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist.
The Bed of Procrustes: Philosophical and Practical Aphorisms, Introduction (2010)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #categories #categorization #knowledge #mind #narratives #oversimplification #patterns #shortcut #simplicity #tropes #understanding
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A quotation from Nicholas Taleb
We humans, facing limits of knowledge, and things we do not observe, the unseen and the unknown, resolve the tension by squeezing life and the world into crisp commoditized ideas, reductive categories, specific vocabularies, and prepackaged narratives, which, on the occasion, has explosive consequences.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist.
The Bed of Procrustes: Philosophical and Practical Aphorisms, Introduction (2010)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #categories #categorization #knowledge #mind #narratives #oversimplification #patterns #shortcut #simplicity #tropes #understanding
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Because our minds need to reduce information, we are more likely to try to squeeze a phenomenon into the Procrustean bed of a crisp and known category (amputating the unknown), rather than suspend categorization, and make it tangible. Thanks to our detections of false patterns, along with real ones, what is random will appear less random and more certain — our overactive brains are more likely to impose the wrong, simplistic, narrative than no narrative at all.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist.
The Bed of Procrustes: Philosophical and Practical Aphorisms, “Postface” (2010)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #assumption #categorization #cognition #explanation #information #mind #model #narrative #oversimplification #patterns #thought #understanding
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Because our minds need to reduce information, we are more likely to try to squeeze a phenomenon into the Procrustean bed of a crisp and known category (amputating the unknown), rather than suspend categorization, and make it tangible. Thanks to our detections of false patterns, along with real ones, what is random will appear less random and more certain — our overactive brains are more likely to impose the wrong, simplistic, narrative than no narrative at all.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist.
The Bed of Procrustes: Philosophical and Practical Aphorisms, “Postface” (2010)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #assumption #categorization #cognition #explanation #information #mind #model #narrative #oversimplification #patterns #thought #understanding
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Because our minds need to reduce information, we are more likely to try to squeeze a phenomenon into the Procrustean bed of a crisp and known category (amputating the unknown), rather than suspend categorization, and make it tangible. Thanks to our detections of false patterns, along with real ones, what is random will appear less random and more certain — our overactive brains are more likely to impose the wrong, simplistic, narrative than no narrative at all.
Nassim Nicholas Taleb (b. 1960) Lebanese-American essayist, statistician, risk analyst, aphorist.
The Bed of Procrustes: Philosophical and Practical Aphorisms, “Postface” (2010)Sourcing, notes: wist.info/taleb-nassim-nichola…
#quote #quotes #quotation #assumption #categorization #cognition #explanation #information #mind #model #narrative #oversimplification #patterns #thought #understanding
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#Proof of #Perfection : Medium
#Scientists figured out the #Optimal cup of #Coffee : Pop Sci
#Physicists describe #Exotic ‘#Paraparticles’ that defy #Categorization : Nature
Check our latest #KnowledgeLinks
-
#Proof of #Perfection : Medium
#Scientists figured out the #Optimal cup of #Coffee : Pop Sci
#Physicists describe #Exotic ‘#Paraparticles’ that defy #Categorization : Nature
Check our latest #KnowledgeLinks
-
#Proof of #Perfection : Medium
#Scientists figured out the #Optimal cup of #Coffee : Pop Sci
#Physicists describe #Exotic ‘#Paraparticles’ that defy #Categorization : Nature
Check our latest #KnowledgeLinks
-
#Proof of #Perfection : Medium
#Scientists figured out the #Optimal cup of #Coffee : Pop Sci
#Physicists describe #Exotic ‘#Paraparticles’ that defy #Categorization : Nature
Check our latest #KnowledgeLinks
-
#Proof of #Perfection : Medium
#Scientists figured out the #Optimal cup of #Coffee : Pop Sci
#Physicists describe #Exotic ‘#Paraparticles’ that defy #Categorization : Nature
Check our latest #KnowledgeLinks
-
Jenny's 20 Den comics quadrant
#quadrant #comic #categorization
[The New Yorker]
LAWFUL GOOD---
[Saturday Morning Breakfast Cereal]
NEUTRAL GOOD----
[Альфина]
CHAOTIC GOOD---
[The Bus by Paul Kirschner]
LAWFUL NEUTRAL---
[Garfield]
TRUE NEUTRAL---
[xkcd]
CHAOTIC NEUTRAL---
[Jenny's 20 Den]
LAWFUL EVIL---
[Дюран]
NEUTRAL EVIL---
[Cyanide & Happiness]
CHAOTIC EVIL -
Jenny's 20 Den comics quadrant
#quadrant #comic #categorization
[The New Yorker]
LAWFUL GOOD---
[Saturday Morning Breakfast Cereal]
NEUTRAL GOOD----
[Альфина]
CHAOTIC GOOD---
[The Bus by Paul Kirschner]
LAWFUL NEUTRAL---
[Garfield]
TRUE NEUTRAL---
[xkcd]
CHAOTIC NEUTRAL---
[Jenny's 20 Den]
LAWFUL EVIL---
[Дюран]
NEUTRAL EVIL---
[Cyanide & Happiness]
CHAOTIC EVIL -
Jenny's 20 Den comics quadrant
#quadrant #comic #categorization
[The New Yorker]
LAWFUL GOOD---
[Saturday Morning Breakfast Cereal]
NEUTRAL GOOD----
[Альфина]
CHAOTIC GOOD---
[The Bus by Paul Kirschner]
LAWFUL NEUTRAL---
[Garfield]
TRUE NEUTRAL---
[xkcd]
CHAOTIC NEUTRAL---
[Jenny's 20 Den]
LAWFUL EVIL---
[Дюран]
NEUTRAL EVIL---
[Cyanide & Happiness]
CHAOTIC EVIL -
When I was basically told off by some people who thought I was ‘looking for a cookie’, then dug into the history and growth of ‘Some Other Race’ in the U.S. Census, I was surprised. I had no idea how many people didn’t fit neatly into the categorizations of race existed in the United States, and how much they had grown.
It’s a far cry from when I grew up. Of course, because the people who claim some other race are so diverse, there is not much to connect them other than the U.S. Census which is as flawed as the concept of ‘race’.
Speaking for myself, I just don’t like being pigeon-holed, sent into a color-coded box to make someone else happy. That’s not my identity and it never will be.
It is simply extraordinary that there are so many people out there with their own stories. People who group people together diminish the stories of individual identity, of not feeling like one fits in to a system that tries to force people to fit in. It begs the question why the system exists in the first place.
In perusing around some more on the topic, I came across the famous Timothy Leary quote, the last 3 sentences of which are in the pictures.
I could not find the source of the quote, which bothers me a bit because it’s something that, before reading the quote, I lived.
“Admit it. You aren’t like them. You’re not even close. You may occasionally dress yourself up as one of them, watch the same mindless television shows as they do, maybe even eat the same fast food sometimes. But it seems that the more you try to fit in, the more you feel like an outsider, watching the “normal people” as they go about their automatic existences. For every time you say club passwords like “Have a nice day” and “Weather’s awful today, eh?”, you yearn inside to say forbidden things like “Tell me something that makes you cry” or “What do you think deja vu is for?”. Face it, you even want to talk to that girl in the elevator. But what if that girl in the elevator (and the balding man who walks past your cubicle at work) are thinking the same thing? Who knows what you might learn from taking a chance on conversation with a stranger? Everyone carries a piece of the puzzle. Nobody comes into your life by mere coincidence. Trust your instincts. Do the unexpected. Find the others…”
Timothy Leary (attrib), no source found.
The others. Generally, the most interesting people I have found could resonate with this quote. The ‘others’. The ones who defy the need to fit in, who identify more as themselves than what others expect them to be, either by peer pressure or societal pressure to belong to a group. Those in groups are at least partly defined by the groups they identify with, and all that comes with it.
It’s not about ‘race’, or any of that other nonsense – and it is nonsense. To be defined by a color or nationality or a job description is limiting. If all you are is defined by society, then you have been shaped by society more than you are shaping it.
Leary was right. We do need to find the others, the gente real, the real people out there who don’t want to be defined by someone else’s hatreds or acceptances. Maybe, just maybe, if we connect, we can create a better system, more granular, of people who have more to contribute to us solving our puzzles than attempts at hierarchy that implicitly demean.
We have more original cookies, I think, or at least we don’t pretend someone’s cookies are better than others based on categories.
https://realityfragments.com/2024/04/19/find-the-others/
#categorization #Culture #hierarchy #humanity #individuality #life #others #perspective #race #racism #society #SomeOtherRace #TimothyLeary
-
When I was basically told off by some people who thought I was ‘looking for a cookie’, then dug into the history and growth of ‘Some Other Race’ in the U.S. Census, I was surprised. I had no idea how many people didn’t fit neatly into the categorizations of race existed in the United States, and how much they had grown.
It’s a far cry from when I grew up. Of course, because the people who claim some other race are so diverse, there is not much to connect them other than the U.S. Census which is as flawed as the concept of ‘race’.
Speaking for myself, I just don’t like being pigeon-holed, sent into a color-coded box to make someone else happy. That’s not my identity and it never will be.
It is simply extraordinary that there are so many people out there with their own stories. People who group people together diminish the stories of individual identity, of not feeling like one fits in to a system that tries to force people to fit in. It begs the question why the system exists in the first place.
In perusing around some more on the topic, I came across the famous Timothy Leary quote, the last 3 sentences of which are in the pictures.
I could not find the source of the quote, which bothers me a bit because it’s something that, before reading the quote, I lived.
“Admit it. You aren’t like them. You’re not even close. You may occasionally dress yourself up as one of them, watch the same mindless television shows as they do, maybe even eat the same fast food sometimes. But it seems that the more you try to fit in, the more you feel like an outsider, watching the “normal people” as they go about their automatic existences. For every time you say club passwords like “Have a nice day” and “Weather’s awful today, eh?”, you yearn inside to say forbidden things like “Tell me something that makes you cry” or “What do you think deja vu is for?”. Face it, you even want to talk to that girl in the elevator. But what if that girl in the elevator (and the balding man who walks past your cubicle at work) are thinking the same thing? Who knows what you might learn from taking a chance on conversation with a stranger? Everyone carries a piece of the puzzle. Nobody comes into your life by mere coincidence. Trust your instincts. Do the unexpected. Find the others…”
Timothy Leary (attrib), no source found.
The others. Generally, the most interesting people I have found could resonate with this quote. The ‘others’. The ones who defy the need to fit in, who identify more as themselves than what others expect them to be, either by peer pressure or societal pressure to belong to a group. Those in groups are at least partly defined by the groups they identify with, and all that comes with it.
It’s not about ‘race’, or any of that other nonsense – and it is nonsense. To be defined by a color or nationality or a job description is limiting. If all you are is defined by society, then you have been shaped by society more than you are shaping it.
Leary was right. We do need to find the others, the gente real, the real people out there who don’t want to be defined by someone else’s hatreds or acceptances. Maybe, just maybe, if we connect, we can create a better system, more granular, of people who have more to contribute to us solving our puzzles than attempts at hierarchy that implicitly demean.
We have more original cookies, I think, or at least we don’t pretend someone’s cookies are better than others based on categories.
https://realityfragments.com/2024/04/19/find-the-others/
#categorization #Culture #hierarchy #humanity #individuality #life #others #perspective #race #racism #society #SomeOtherRace #TimothyLeary
-
The "is a hotdog a sandwich" question is fascinating to me, not because it doesn't have an obvious answer (it does: "fuck no, why would you ask such a stupid question"), but because once you ask folks to justify why or why not, they start producing these bizarre taxonomies based on the features of a sandwich, trying to discover what sandwichness truly means.
1/3 cont...
#categorization #sandwich #AristotleWasAWeirdNerd #hotdog #TheEternalDebateContinues
-
The "is a hotdog a sandwich" question is fascinating to me, not because it doesn't have an obvious answer (it does: "fuck no, why would you ask such a stupid question"), but because once you ask folks to justify why or why not, they start producing these bizarre taxonomies based on the features of a sandwich, trying to discover what sandwichness truly means.
1/3 cont...
#categorization #sandwich #AristotleWasAWeirdNerd #hotdog #TheEternalDebateContinues
-
The "is a hotdog a sandwich" question is fascinating to me, not because it doesn't have an obvious answer (it does: "fuck no, why would you ask such a stupid question"), but because once you ask folks to justify why or why not, they start producing these bizarre taxonomies based on the features of a sandwich, trying to discover what sandwichness truly means.
1/3 cont...
#categorization #sandwich #AristotleWasAWeirdNerd #hotdog #TheEternalDebateContinues
-
The "is a hotdog a sandwich" question is fascinating to me, not because it doesn't have an obvious answer (it does: "fuck no, why would you ask such a stupid question"), but because once you ask folks to justify why or why not, they start producing these bizarre taxonomies based on the features of a sandwich, trying to discover what sandwichness truly means.
1/3 cont...
#categorization #sandwich #AristotleWasAWeirdNerd #hotdog #TheEternalDebateContinues
-
Apologies, as this will be a bit #rambling, but it will come back to #Canadian #politics, I promise.
First, the #categorization of #political views along a single left-right #axis is almost #useless. This has long been known, and alternatives exist that present a much more accurate picture, but the traditional #media is #addicted to "#left this" and "#right that" and is lazy, so they'll probably never get better.
One #alternative was developed by Jerry #Pournelle.
1/x
-
Apologies, as this will be a bit #rambling, but it will come back to #Canadian #politics, I promise.
First, the #categorization of #political views along a single left-right #axis is almost #useless. This has long been known, and alternatives exist that present a much more accurate picture, but the traditional #media is #addicted to "#left this" and "#right that" and is lazy, so they'll probably never get better.
One #alternative was developed by Jerry #Pournelle.
1/x
-
Apologies, as this will be a bit #rambling, but it will come back to #Canadian #politics, I promise.
First, the #categorization of #political views along a single left-right #axis is almost #useless. This has long been known, and alternatives exist that present a much more accurate picture, but the traditional #media is #addicted to "#left this" and "#right that" and is lazy, so they'll probably never get better.
One #alternative was developed by Jerry #Pournelle.
1/x
-
Apologies, as this will be a bit #rambling, but it will come back to #Canadian #politics, I promise.
First, the #categorization of #political views along a single left-right #axis is almost #useless. This has long been known, and alternatives exist that present a much more accurate picture, but the traditional #media is #addicted to "#left this" and "#right that" and is lazy, so they'll probably never get better.
One #alternative was developed by Jerry #Pournelle.
1/x
-
Apologies, as this will be a bit #rambling, but it will come back to #Canadian #politics, I promise.
First, the #categorization of #political views along a single left-right #axis is almost #useless. This has long been known, and alternatives exist that present a much more accurate picture, but the traditional #media is #addicted to "#left this" and "#right that" and is lazy, so they'll probably never get better.
One #alternative was developed by Jerry #Pournelle.
1/x
-
TIL: Eleanor Rosch profoundly influenced cognitive psychology with her prototype theory, a Copernican revolution in the theory of categorization for its departure from the traditional Aristotelian categories.
Fun fact: While a student, “Rosch had planned for years to go to graduate school in philosophy, but a year with Wittgenstein, she says, “cured her” of philosophy completely.” 🤣
-
TIL: Eleanor Rosch profoundly influenced cognitive psychology with her prototype theory, a Copernican revolution in the theory of categorization for its departure from the traditional Aristotelian categories.
Fun fact: While a student, “Rosch had planned for years to go to graduate school in philosophy, but a year with Wittgenstein, she says, “cured her” of philosophy completely.” 🤣
-
TIL: Eleanor Rosch profoundly influenced cognitive psychology with her prototype theory, a Copernican revolution in the theory of categorization for its departure from the traditional Aristotelian categories.
Fun fact: While a student, “Rosch had planned for years to go to graduate school in philosophy, but a year with Wittgenstein, she says, “cured her” of philosophy completely.” 🤣
-
TIL: Eleanor Rosch profoundly influenced cognitive psychology with her prototype theory, a Copernican revolution in the theory of categorization for its departure from the traditional Aristotelian categories.
Fun fact: While a student, “Rosch had planned for years to go to graduate school in philosophy, but a year with Wittgenstein, she says, “cured her” of philosophy completely.” 🤣
-
TIL: Eleanor Rosch profoundly influenced cognitive psychology with her prototype theory, a Copernican revolution in the theory of categorization for its departure from the traditional Aristotelian categories.
Fun fact: While a student, “Rosch had planned for years to go to graduate school in philosophy, but a year with Wittgenstein, she says, “cured her” of philosophy completely.” 🤣
-
In an age when we're all just entries in some algorithmic spreadsheet somewhere, be a platypus and mess up the categories.
Redbubble is 20% off right now so this fellow is new in the shop to celebrate - get you a sticker or something groovy.
https://www.redbubble.com/shop/ap/141170295
#MastoArt #FediArt #Platypus #Algorithm #Categorization #Inspiration #Encouragement #OriginalArt #CreativeToots
-
In an age when we're all just entries in some algorithmic spreadsheet somewhere, be a platypus and mess up the categories.
Redbubble is 20% off right now so this fellow is new in the shop to celebrate - get you a sticker or something groovy.
https://www.redbubble.com/shop/ap/141170295
#MastoArt #FediArt #Platypus #Algorithm #Categorization #Inspiration #Encouragement #OriginalArt #CreativeToots
-
In an age when we're all just entries in some algorithmic spreadsheet somewhere, be a platypus and mess up the categories.
Redbubble is 20% off right now so this fellow is new in the shop to celebrate - get you a sticker or something groovy.
https://www.redbubble.com/shop/ap/141170295
#MastoArt #FediArt #Platypus #Algorithm #Categorization #Inspiration #Encouragement #OriginalArt #CreativeToots
-
In an age when we're all just entries in some algorithmic spreadsheet somewhere, be a platypus and mess up the categories.
Redbubble is 20% off right now so this fellow is new in the shop to celebrate - get you a sticker or something groovy.
https://www.redbubble.com/shop/ap/141170295
#MastoArt #FediArt #Platypus #Algorithm #Categorization #Inspiration #Encouragement #OriginalArt #CreativeToots
-
Are you coming to the International Convention of Psychological Science in Brussels next week?
Come to our BAPS invited symposium on Categorization across Fields: Insights from Learning, Cognition, and Perception!Thursday, March 9
4:30PM - 5:50PM
Studio 201 A+BPresentations by Jonas Zaman, Matías Osta-Vélez, Eline Van Geert, and Steven Verheyen, followed by a general discussion
-
Are you coming to the International Convention of Psychological Science in Brussels next week?
Come to our BAPS invited symposium on Categorization across Fields: Insights from Learning, Cognition, and Perception!Thursday, March 9
4:30PM - 5:50PM
Studio 201 A+BPresentations by Jonas Zaman, Matías Osta-Vélez, Eline Van Geert, and Steven Verheyen, followed by a general discussion