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Record W2995448967 · doi:10.1111/joms.12547

Coupling High Self‐Perceived Creativity and Successful Newcomer Adjustment in Organizations: The Role of Supervisor Trust and Support for Authentic Self‐Expression

2019· article· en· W2995448967 on OpenAlexaff
Lucas Dufour, Massimo Maoret, Francesco Montani

Bibliographic record

VenueJournal of Management Studies · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSupervisorCreativityPsychologyPerceptionSocial psychologySocializationMediationExpression (computer science)ManagementComputer scienceSociology

Abstract

fetched live from OpenAlex

Abstract This study addresses how supervisors can facilitate the socialization of newcomers with high self‐perceived creativity into their new jobs. We combine self‐verification theory and current literature on socialization in a dual‐stage moderated mediation model where a) newcomer self‐perceived creativity interacts with supervisor trust in the newcomer to trigger supervisor perception of newcomer creativity; and b) supervisor perception of newcomer creativity, in turn, interacts with supervisor support for newcomer authentic self‐expression to impact newcomer adjustment outcomes (i.e., task performance, job satisfaction, and stress symptoms). A two‐wave, multisource study of 146 newcomer–supervisor dyads provides support for our predictions, suggesting that high levels of supervisor trust and support for authentic self‐expression serve as moderating conditions allowing supervisor perception of newcomer creativity to positively mediate the relationship between newcomer self‐perceived creativity and newcomer adjustment.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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

Citations38
Published2019
Admission routes1
Has abstractyes

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