MétaCan
Menu
Back to cohort
Record W3159257248 · doi:10.1108/edi-03-2021-0071

Four ways forward in studying sex-based harassment

2021· article· en· W3159257248 on OpenAlex
Jennifer L. Berdahl, Barnini Bhattacharyya

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEquality Diversity and Inclusion An International Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHarassmentOriginalityScholarshipValue (mathematics)Diversity (politics)Inclusion (mineral)SociologyPerspective (graphical)Action (physics)Conceptual frameworkSocial psychologyEpistemologyPsychologySocial sciencePolitical scienceComputer scienceQualitative researchArtificial intelligenceLaw

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to identify promising themes of the papers in the special issues of Equality, Diversity and Inclusion dedicated to advancing scholarship on sex-based harassment. Design/methodology/approach A conceptual overview of the research pertaining to these themes and an analysis of the special issues papers' contributions to these themes. Findings Four themes that represent important but relatively neglected lines of inquiry into sex-based harassment are identified. These are (1) the psychology of harassment, (2) organizational culture and networks, (3) the invisible majority and (4) the importance of collective action. Originality/value The paper offers an expert perspective on the state of research related to sex-based harassment and four themes that are important to moving it forward.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0000.001
Open science0.0000.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.157
GPT teacher head0.390
Teacher spread0.233 · 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