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Record W3199756224 · doi:10.1037/hop0000202

Adolphe Quetelet and the legacy of the “average man” in psychology.

2021· article· en· W3199756224 on OpenAlexaff
Donna Tafreshi

Bibliographic record

VenueHistory of Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsPolymathPsycINFOPsychologyDistribution (mathematics)AstronomerDeterminismSociologySocial scienceEpistemologyHistoryLawMEDLINEPhilosophyArt historyMathematics

Abstract

fetched live from OpenAlex

) and, as such, argued that the average value of a distribution should be of primary concern in the study of human attributes. In the present article, I examine the influences that these ideas had on the methodological practices of late 19th- and early 20th- century psychologists. I illustrate how the dominant methodological approach implemented by psychologists in the early 20th century was deeply rooted in the demography of Quetelet's social statistics. In particular, I argue that psychologists' adoption of the Neo-Galtonian model of research was successful because it embraced Quetelet's determinism, emphasis on average values, and grouping of distributions based on type. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.025
Scholarly communication0.0060.014
Open science0.0010.002
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0100.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.339
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2021
Admission routes1
Has abstractyes

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