MétaCan
Menu
Back to cohort
Record W3211740982 · doi:10.1177/09593543211057098

Psychologising meritocracy: A historical account of its many guises

2021· article· en· W3211740982 on OpenAlexaboutno aff
Francesca Trevisan, Patrice Rusconi, Paul Hanna, Peter Hegarty

Bibliographic record

VenueTheory & Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsMeritocracyIdeologySociologyEpistemologyPositive economicsSocial scienceLawPoliticsPolitical scienceEconomicsPhilosophy

Abstract

fetched live from OpenAlex

Measured by psychologists, conceived in critical terms, popularised as satire, and exploited by politicians, meritocracy is a dilemmatic concept that has changed its meanings throughout history. Social psychologists have conceptualised and operationalised meritocracy both as an ideology that justifies inequality and as a justice principle based on equity. These two conceptualisations express opposing ideas about the merit of meritocracy and are both freighted ideologically. We document how this dilemma of meritocracy’s merit developed from meritocracy’s inception as a critical concept among UK sociologists in the 1950s to its operationalisation by U.S. and Canadian social psychologists at the end of the 20th century. We highlight the ways in which meritocracy was originally utilised, in part, to critique the measurement of merit via IQ tests, but ironically became a construct that, through its psychologisation, also required measurement. Through the operationalisation of meritocracy, social psychologists obscured the possibility of critiquing meritocracy and missed the opportunity to offer alternatives to a system that has been legitimised by their own work. A social psychology of meritocracy should take into consideration the ideological debate around its meaning and value and the implications of its measurement and study.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.052
GPT teacher head0.399
Teacher spread0.348 · 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; both teacher heads agree on what is shown here.

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

Citations15
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueTheory & PsychologySame topicAcademic and Historical Perspectives in PsychologyFrench-language works237,207