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Configuring and Contextualising HR Systems: An Empirical Study of Manufacturing SMEs

2008· article· en· W1556637836 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuemanagement revue · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPublishingEmpirical researchWork (physics)Qualitative researchKnowledge managementPeer reviewHuman resource managementEngineering ethicsIndustrial relationsBusinessSociologyManagementPsychologyProcess managementEngineeringPolitical scienceSocial scienceComputer scienceEpistemologyMechanical engineeringPhilosophyEconomics

Abstract

fetched live from OpenAlex

Human resource management (HRM) has become for SMEs a critical factor of adaptation to an increasingly complex and uncertain business environment. Founded on open systems and contingency theory, the present study seeks to identify configurations of HR systems in manufacturing SMEs, and to determine the extent to which these configurations are associated to the environmental and organisational context. Survey data analysis of 176 manufacturing SMEs revealed three configurations of HR systems, namely a "strategic-high-commitment system", a "functional-high-commitment system", and a "traditional-low-commitment system". Differences in these systems are associated to variables that reflect the SMEs' environmental, organisational and technological context.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.053
GPT teacher head0.272
Teacher spread0.219 · 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