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Outcomes of Bridge Employment: A Psychological Contract Theory Perspective

2017· article· en· W2766237601 on OpenAlexaff
Bishakha Mazumdar, Amy M. Warren, Travor C. Brown, Kathryne E. Dupré

Bibliographic record

VenueAcademy of Management Proceedings · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBridge (graph theory)Psychological contractJob satisfactionLife satisfactionPerspective (graphical)PsychologyCitizenshipSurvey data collectionPopulation ageingPopulationSocial psychologyBusinessSociologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

A disproportionate rise in the aging population worldwide has resulted in widespread concern about stagnant economic growth and unstable social support systems. Academics and policy makers alike suggest that a solution to this challenge is prolonging the working life of older people. Bridge employment, or employment after retirement, is one way to extend working life. Although research on bridge employment has gained momentum in recent years, most studies use archival data, very few studies look at modalities and outcomes of bridge employment engagement, and even fewer studies utilize a theoretical framework to examine the bridge employment phenomenon. We collected survey data from 195 bridge employees, and found that psychological contract fulfillment was a significant predictor of work and well-being outcomes, including life satisfaction, marital adjustment quality, job satisfaction, commitment, organizational citizenship behavior, co- worker intimacy, and intention to continue working for the employing organization. These results suggest that psychological contract theory is important to understanding how bridge employees perceive and react to their employment arrangements.

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)0.002
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 score0.616
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.234
GPT teacher head0.479
Teacher spread0.245 · 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
Published2017
Admission routes1
Has abstractyes

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