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Selection Practices in <scp>C</scp>anadian Firms: An empirical investigation

2011· article· en· W1480306746 on OpenAlexaff
Sara L. Mann, James Chowhan

Bibliographic record

VenueInternational Journal of Selection and Assessment · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEmployer Branding and e-HRM
Canadian institutionsMcMaster UniversityUniversity of Guelph
Fundersnot available
KeywordsSelection (genetic algorithm)PsychologyPersonnel selectionTest (biology)PersonalityLogitHuman resource managementEmpirical researchApplied psychologySocial psychologyMarketingEconometricsManagementStatisticsBusinessEconomicsComputer scienceArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Using 7 years of data from S tatistics C anada's W orkplace and E mployee S urvey, this study examined the types of selection tools used with 23,639 employees in 6,693 C anadian firms. While 79% of these employees were given an interview during the selection process, only 10% were given a test on job‐related knowledge and 9% were given a personality test. Using logit analysis, job‐ and organization‐level variables were examined as predictors of the type of selection tools used. The size of the organization, an in‐house human resource department, the presence of a union and occupation were significant predictors of the use of a test on job‐related knowledge in the selection process. The implications and plausible explanations of this theory to practice gap are discussed.

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)0.001
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 score0.038
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.083
GPT teacher head0.350
Teacher spread0.268 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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