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Record W2191811643 · doi:10.1111/jasp.12363

(Re)Applying social psychology to organizational work, well‐being, and leadership

2015· article· en· W2191811643 on OpenAlexaff
David E. Rast, Carolyn Axtell, Stephen McGlynn

Bibliographic record

VenueJournal of Applied Social Psychology · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyIndustrial and organizational psychologyOrganizational behaviorSocial psychologyPower (physics)Organizational studiesPsychological researchEpistemologyOrganizational commitment

Abstract

fetched live from OpenAlex

Abstract Research on organizational behavior is fundamentally an application of social psychology theory and phenomena. While much of organizational psychology is inherently grounded in social psychological research, these two disciplines are largely disconnected from one another. More visibility of the commonalities may encourage discussion, collaboration, and integration between these two fields—an integration that will only benefit each discipline. The present article briefly reviews the historic overlap between these disciplines, the resulting divide between them, and then discusses recent developments demonstrating the potential power of reconnecting social psychology with organizational‐relevant research. We then examine how the six empirical articles in this Special Issue benefit from applying social psychological theory to organizational research. We will conclude by identifying potential areas ripe for future research.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.089
GPT teacher head0.326
Teacher spread0.238 · 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 teacher head, not a consensus.

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

Citations2
Published2015
Admission routes1
Has abstractyes

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