MétaCan
Menu
Back to cohort
Record W2766628898 · doi:10.1108/cdi-01-2017-0017

Networking and development idiosyncratic deals

2017· article· en· W2766628898 on OpenAlexaff
Sylvie Guerrero, Hélène Challiol Jeanblanc

Bibliographic record

VenueCareer Development International · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsNegotiationOriginalityContext (archaeology)PsychologyMediationValue (mathematics)Public relationsSocial psychologySociologyKnowledge managementPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to explore the antecedents of development idiosyncratic deals (i-deals) from an organizational politics and a situationist perspective. The paper tests a moderated mediation model in which networking skills is indirectly related to development i-deal in a context of high hierarchical plateau. Design/methodology/approach The authors test the research model with a sample of 252 engineers, 88 percent male, who work in an economically wealthy region of France and who are thus well positioned to negotiate development i-deals. Findings The authors lead analyses with the Preacher et al. ’s macros on SPSS. Results support the hypotheses. The authors find that support-seeking behaviors partially mediate the relationship between networking skills and development i-deals, and that this relationship is significant only in a context of high plateauing. Originality/value Overall, this study contributes to a deeper understanding of i-deal antecedents by bridging the literatures on i-deals and careers. It also shows that socially skilled employees are able to seek support and in turn, to proactively negotiate development i-deals. This process is a way to cope with perceptions of hierarchical plateau.

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 score0.389
Threshold uncertainty score0.909

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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.252
Teacher spread0.209 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCareer Development InternationalSame topicJob Satisfaction and Organizational BehaviorFrench-language works237,207