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Record W2414767726 · doi:10.1177/0894845316652251

Can “Temps” Secure Future Employment? Investigating the Relationship Between Proactive Behaviors and Employers’ Rehiring Decision

2016· article· en· W2414767726 on OpenAlexaff
Marie‐Ève Lapalme, Olivier Doucet, Andréa Gill, Gilles Simard

Bibliographic record

VenueJournal of Career Development · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsHEC MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsSupervisorCLARITYPsychologySocial psychologyBossSocializationAgency (philosophy)Quality (philosophy)Management

Abstract

fetched live from OpenAlex

This study examines how the adoption of proactive socialization behaviors by temporary agency workers is related to contract renewal intention of the supervisor in the client organization in which they are assigned. We propose that the adoption of such behaviors will be associated with a favorable performance evaluation from the supervisor in the client organization, and in turn, to his or her contract renewal intention through two mechanisms, namely, role clarity and leader–member exchange (LMX), which refers to the quality of the relationship between the temporary worker and his or her supervisor. Data were collected from 217 worker–supervisor dyads. Results indicate that information-seeking behavior is related to performance evaluation through role clarity. This indirect relationship is however negative, as greater role clarity relates negatively to performance evaluation. Our results also show that LMX acts as a mediator between feedback seeking, boss-relationship building, and performance. Finally, favorable performance evaluation is positively associated with contract renewal intention.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.256
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2016
Admission routes1
Has abstractyes

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