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What If Industrial–Organizational Psychology Decided to Take Workplace Decisions Seriously?

2010· article· en· W2042331900 on OpenAlex
Reeshad S. Dalal, Silvia Bonaccio, Scott Highhouse, Daniel R. Ilgen, Susan Mohammed, Jerel E. Slaughter

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

VenueIndustrial and Organizational Psychology · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPremiseConversationPsychologyPublic relationsField (mathematics)Applied psychologyEngineering ethicsPolitical scienceEpistemologyEngineering

Abstract

fetched live from OpenAlex

The major premise of this article is that increased exposure to—and increased application of—theories, methods, and findings from the judgment and decision-making (JDM) field will aid industrial–organizational psychology and organizational behavior (IOOB) researchers and practitioners in studying workplace decisions. To this end, we first provide evidence of the lack of cross-fertilization between JDM and IOOB and then provide an overview of the JDM research literature. Next, with the aid of a panel of prominent IOOB scholars who share JDM interests, we discuss the philosophical and methodological traditions in IOOB and JDM, the areas in which IOOB has already been enriched by JDM as well as the areas in which it might be further enriched in the future, ways of increasing cross-fertilization from JDM to IOOB, and ways in which IOOB can in turn contribute to JDM. Through this focal article, we hope to spark conversation and ultimately engender more cross-fertilization between JDM and IOOB.

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)0.003
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.003

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 head0.187
GPT teacher head0.422
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