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Record W2898563287 · doi:10.3917/rsg.291.0013

La mesure de l’attraction dans les organisations situées en région périphérique : vers un modèle de l’attraction régionale des travailleurs du savoir

2018· article· fr· W2898563287 on OpenAlexaff
Andrée‐Anne Deschênes, Catherine Beaudry, Josée Laflamme, Mounir Aguir

Bibliographic record

Venue˜La œRevue des sciences de gestion/˜La œRevue des sciences de gestion, Direction et gestion · 2018
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsUniversité du Québec à RimouskiUniversité Laval
Fundersnot available
KeywordsMolecular biologyChemistryPhysicsBiology

Abstract

fetched live from OpenAlex

Les organisations situées dans les régions périphériques québécoises sont préoccupées par leur capacité à attirer des travailleurs qualifiés. Toutefois, peu d’études s’intéressent aux déterminants de l’attraction régionale. L’objectif de cet article est de développer une mesure de l’attraction régionale et de confirmer sa structure factorielle chez une population de futurs travailleurs du savoir. Un questionnaire a été distribué aux étudiants de huit universités québécoises (n = 876). Une analyse factorielle confirmatoire ainsi qu’une vérification de l’invariance selon le sexe et la région d’origine ont été effectuées. Les résultats de l’analyse factorielle confirmatoire supportent la structure d’un modèle de l’attraction régionale à trois dimensions (S-B X2 = 156,76 ; DL = 33 ; CFI =, 956 ; NNFI =, 941 ; RMSEA =, 065 ; CAIC = -99,83), soit l’environnement économique, la qualité de vie et la culture régionale. L’analyse multigroupe confirme que l’échelle de mesure s’applique uniformément selon le genre et la région d’origine.

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)0.018
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0090.010
Scholarly communication0.0030.008
Open science0.0010.000
Research integrity0.0010.002
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 head0.128
GPT teacher head0.312
Teacher spread0.183 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venue˜La œRevue des sciences de gestion/˜La œRevue des sciences de gestion, Direction et gestionSame topicCustomer Service Quality and LoyaltyFrench-language works237,207