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STATE OF SCIENCE IN INDUSTRIAL AND ORGANIZATIONAL PSYCHOLOGY: A REVIEW OF SELF‐REPORTED LIMITATIONS

2010· review· en· W2092712913 on OpenAlexaff
Stéphane Brutus, Harjinder Gill, Kris Duniewicz

Bibliographic record

VenuePersonnel Psychology · 2010
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicOccupational and Professional Licensing Regulation
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOperationalizationPsychologyIndustrial and organizational psychologyApplied psychologyPsychological researchConsulting psychologyFocus (optics)Social psychologySchool psychologyEpistemology

Abstract

fetched live from OpenAlex

This study investigated self‐reported limitations of published papers as an alternative and novel operationalization of the state of science of industrial and organizational (I‐O) psychology. A content analysis was conducted of the reported limitations in every I‐O psychology articles published in the Academy of Management Journal, the Journal of Applied Psychology, and Personnel Psychology between 1995 and 2008 (N= 2,402). Articles were coded for the number and types of limitations reported, characteristics of the research design, and topic area. Threats to internal validity were the most often reported limitations. In addition, variations were detected in the reporting of limitations over time, indicating a subtle but steady shift in the focus of I‐O psychology research. Implications of these results for the science and practice of I‐O psychology and for the use of self‐reported limitations in scientific communication are discussed.

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)0.063
metaresearch head score (Gemma)0.187
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.937
Threshold uncertainty score0.333

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0630.187
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0170.017
Science and technology studies0.0010.003
Scholarly communication0.0040.005
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.229
GPT teacher head0.393
Teacher spread0.164 · 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 designSystematic review
DomainEvaluation
GenreReview

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

Citations49
Published2010
Admission routes1
Has abstractyes

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