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Record W6991240685

Gender Differences in Professional Development Among AP-LS\nMembers: Results of the Professional Development of Women Survey

2012· article· en· W6991240685 on OpenAlexfundno aff

Bibliographic record

VenueThe Journal of the American Medical Association (JAMA) Network (American Medical Association) · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicOccupational and Professional Licensing Regulation
Canadian institutionsnot available
FundersAmerican Psychology-Law SocietyFlorida Institute of TechnologyMarquette UniversityWilfrid Laurier UniversityTemple UniversityAzusa Pacific UniversityDuquesne UniversityNova Southeastern UniversityDrexel UniversityUniversity of WyomingUniversity of Central FloridaJohn Jay College of Criminal JusticeCreighton UniversityUniversity of North Carolina at Chapel HillUniversity of South FloridaUniversiti Teknologi MalaysiaUniversity of TorontoEmory UniversityUniversity of ReginaSimon Fraser UniversityTexas Tech UniversityUniversity of Central ArkansasFairleigh Dickinson University
KeywordsProfessional developmentProfessional studiesWork (physics)Professional psychologyCareer developmentContinuing professional development
DOInot available

Abstract

fetched live from OpenAlex

The current survey was designed to examine gender differences in professional development among American Psychology - Law Society (AP-LS) members. The survey was based on the University of California, Irvine NSF ADVANCE survey, and examines issues related to work climate, workload, productivity, job satisfaction, work/life balance, and leadership among AP-LS members.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.261
Teacher spread0.235 · 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 designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

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