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Record W2065428899 · doi:10.1002/hrm.10022

The role of human resource management: an exploratory study of cross‐country variance

2002· article· en· W2065428899 on OpenAlexaff
David Bowen, Carmen Galang, Rajnandini Pillai

Bibliographic record

VenueHuman Resource Management · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsContingencyHuman resource managementBusinessCompetitive advantageLinkage (software)Variance (accounting)Strategic human resource planningKnowledge managementMarketingComputer scienceAccounting

Abstract

fetched live from OpenAlex

Abstract We explore how the role of Human Resource Management (HRM) varies across countries on two dimensions. One is how the status of HRM departments may vary (e.g., perceptions of its importance and involvement). Second is whether there is cross‐country strategic HRM (SHRM) in terms of the conventional contingency approach (linking HRM practices to strategy), as well as a resource‐based view of the firm (e.g., developing “organizational capability” as competitive advantage). Results included significant differences in HRM status across countries; significant correlations between status and “organizational capability”; and in Asian countries, a slight tendency for HRM practices to be linked more to a “differentiation” strategy, whereas, in Anglo countries, a strong linkage between HRM practices and “organizational capability.” © 2002 Wiley Periodicals, Inc.

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)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.328
Teacher spread0.286 · 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 designQualitative
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

Citations111
Published2002
Admission routes1
Has abstractyes

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