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Record W2137960395 · doi:10.1111/joms.12120

Why and How Do Employees Break and Bend Confidential Information Protection Rules?

2014· article· en· W2137960395 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Management Studies · 2014
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsSimon Fraser UniversityUniversity of the Fraser Valley
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsConfidentialityFunction (biology)Work (physics)Forcing (mathematics)BusinessScholarshipCompliance (psychology)Public relationsBent molecular geometryKnowledge managementComputer scienceLawComputer securityPolitical sciencePsychologySocial psychologyEngineering

Abstract

fetched live from OpenAlex

ABSTRACT Organizations cannot function effectively if their employees do not follow organizational rules and policies. In this paper, we explore why and how employees in two high‐tech organizations often broke or bent rules designed to protect their employers' confidential information (CI). The CI protection rules sometimes imposed requirements that disrupted employees' work, forcing employees to choose between CI rule compliance and doing their work effectively and efficiently. Employees in these situations often broke the rules or bent them in ways that enabled employees to meet some of the rules' requirements, while also satisfying other expectations that they faced. We discuss implications of our findings for practice and for future organizational scholarship on rule following.

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)0.001
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: none
Teacher disagreement score0.837
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
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 head0.013
GPT teacher head0.234
Teacher spread0.221 · 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