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Record W4402615328 · doi:10.1177/23294906241278618

Modeling Organizations’ Responses to Employee Disclosure at Work: An Organizational Economics Approach

2024· article· en· W4402615328 on OpenAlex

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

VenueBusiness and Professional Communication Quarterly · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsWork (physics)Organisation climatePublic relationsEmployee researchWork environmentEmployee moraleOrganizational theoryPsychologyOrganizational commitmentBusinessEconomicsManagementSocial psychologyJob satisfactionPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Employee disclosure refers to the process of revealing personal information about oneself with others in a workplace setting. This type of disclosure also greatly influences organizational culture, policies, and workplace interactions. Modeling such disclosure scenarios using an organizational economics approach addresses communication challenges faced by businesses dealing with the respective disclosure(s). Further, it allows for uncovering the most effective ways to communicate disclosure procedures and policies to employees and employers. This, in turn, will lead to (a) improved corporate training practices for employee disclosure in business communication settings and (b) increased overall productivity measures for organizational 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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.073
GPT teacher head0.360
Teacher spread0.288 · 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