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Not My Breach! Innovative Ways to Study Psychological Contract Breach and Effects on Meaningfulness

2016· article· en· W2798060117 on OpenAlexaboutno aff
Jos Akkermans, P. Matthijs Bal, Stefan T. Mol

Bibliographic record

VenueAcademy of Management Proceedings · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological contractContext (archaeology)PsychologyBreach of contractExtant taxonWelshSocial psychologyLawPolitical scienceHistoryDamages

Abstract

fetched live from OpenAlex

This symposium aims to introduce innovative ways to understand psychological contracts at work, and in particular the role of contract breach and its aftermath. Extant previous research has shown that employee perceptions of psychological contract breach have profound effects on work attitudes and behaviors, and may have detrimental effects on employees’ experienced meaningfulness of work. There is an upcoming stream of research focusing on contextual factors influencing these relationships as breach is not always negative. However, little is still known concerning the specific context in which breaches occur, how these breaches affect work outcomes, and how organizations and employees may prevent, repair, or resolve the negative impact of breach. This symposium offers five papers which present studies on the context and content of contract breach, show how breach is manifested in the workplace, and how the effects of breach unfold over time. The Different Ways Breach Can Be Repaired: What Can the Organization Do? Presenter: Kevin E. Henderson; U. of St. Thomas Presenter: Elizabeth Welsh; U. of St. Thomas Presenter: Anne O'Leary-Kelly; U. of Arkansas A Unit Climate Perspective on Psychological Contract Breach Presenter: Jos Akkermans; U. of Amsterdam Presenter: Matthijs Bal; U. of Bath Presenter: Simon De Jong; U. of East Anglia Psychological Contract Breach and Its Outcomes: The Devil is in the Detail Presenter: Eloisa Federici; U. of Amsterdam Presenter: Stefan T. Mol; U. of Amsterdam Presenter: Matthijs Bal; U. of Bath Presenter: Marjolein Ten Hoonte; Randstad Group Netherlands Presenter: Claire Revell; Plus Retail The Aftermath of Psychological Contract Violation and Its Implications for Violation Resolution Presenter: Maria Maria; Carnegie Mellon U. Presenter: Yannick Griep; U. of Calgary Prototypical Stories of Commitment After Violation: The Role of Perceived Organizational Support Presenter: Yannick Griep; U. of Calgary Presenter: Maria Maria; Carnegie Mellon U. Presenter: Tim Vantilborgh; Vrije U., Brussel Presenter: Samantha D. Hansen; U. of Toronto Presenter: Joeri Hofmans; Vrije U., Brussel Presenter: Roland Pepermans; Vrije U., Brussel

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.042
GPT teacher head0.273
Teacher spread0.230 · 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 designObservational
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

Citations1
Published2016
Admission routes1
Has abstractyes

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