MétaCan
Menu
Back to cohort
Record W2983364429 · doi:10.1037/amp0000571

Histories of psychology after Stonewall: Introduction to the special issue.

2019· article· en· W2983364429 on OpenAlexaff
Peter Hegarty, Alexandra Rutherford

Bibliographic record

VenueAmerican Psychologist · 2019
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsYork University
Fundersnot available
KeywordsPsycINFOLesbianSexual orientationTransgenderContext (archaeology)Diversity (politics)IdeologyPsychologyPower (physics)History of psychologyPoliticsGender studiesSociologyPsychoanalysisHistoryPolitical scienceLawAnthropology

Abstract

fetched live from OpenAlex

This article introduces the special issue Fifty Years Since Stonewall: The Science and Politics of Sexual Orientation and Gender Diversity. Here, the commemoration of the 1969 Stonewall uprising frames our discussion of issues of representation that arise in commemorating events in general, and events in the history of psychology in particular. We describe how the articles in the special issue expand the existing narratives about the history of lesbian, gay, bisexual, and transgender psychology that are centered in the United States, focused primarily on sexual orientation and often end, rather than begin, in the time of Stonewall. The international scope of the special issue can suggest new ways to particularize histories of psychology since Stonewall that are centered on the United States. We describe the ideological context that shapes the doing of psychology since Stonewall, the telling of the histories of that psychology, and how "the problem of speaking for others" arises in contexts of power, including the curation of the special issue itself. (PsycINFO Database Record (c) 2019 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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.035
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0050.005
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0350.007

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 head0.011
GPT teacher head0.352
Teacher spread0.340 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations19
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAmerican PsychologistSame topicAcademic and Historical Perspectives in PsychologyFrench-language works237,207