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Record W4200478521 · doi:10.1111/1467-8551.12573

Ignoring Leaders who Break Promises or Following God: How Depersonalization and Religious Faith Inform Employees’ Timely Work Efforts

2021· article· en· W4200478521 on OpenAlexaff
Dirk De Clercq, Inam Ul Haq, Muhammad Umer Azeem

Bibliographic record

VenueBritish Journal of Management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsBrock University
Fundersnot available
KeywordsFaithWork (physics)Public relationsPsychological contractSocial psychologyPsychologyPerceptionBusinessPolitical science

Abstract

fetched live from OpenAlex

Abstract This study investigates the relationship between employees’ perceptions of psychological contract breaches and their failure to meet work‐related deadlines, with a particular focus on the mediating role of the depersonalization they assign to organizational authorities and the moderating role of their religious faith. Results based on multisource data, collected among employees and their supervisors in Pakistani organizations, show that an important factor that underpins the connection between beliefs about broken organizational promises and a diminished propensity to finish work on time is that employees depersonalize organizational leaders. This mediating effect is mitigated by employees’ religious faith. For organizations, this study thus identifies a key mechanism – exhibiting indifference to the people in charge – by which employees’ frustrations about resource‐depleting contract breaches may inadvertently escalate into ineffective time management, and it identifies some workers among whom this counterproductive dynamic is less likely, namely, employees who can draw from their religious faith.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.014
GPT teacher head0.215
Teacher spread0.201 · 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 designOther design
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

Citations22
Published2021
Admission routes1
Has abstractyes

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