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Record W1755664270 · doi:10.1111/1744-7941.12080

An exploratory study of the cultural context of organisational climate and human resource practices

2015· article· en· W1755664270 on OpenAlexfundno aff
Renin Varnali

Bibliographic record

VenueAsia Pacific Journal of Human Resources · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsConstruct (python library)Organisation climateExploratory researchContext (archaeology)CollectivismPaternalismHuman resource managementEnvironmental resource managementHuman resourcesKnowledge managementBusinessSociologyPolitical sciencePublic relationsGeographyManagementSocial scienceIndividualismEconomicsComputer science

Abstract

fetched live from OpenAlex

The ‘climate’ construct has an important and long history in organisational science. This study explores a specific type of organisational climate, known as human resource ( HR ) climate, in the context of an organisation operating in T urkey. The competing values framework is used to interpret the findings regarding the nature of HR climate, and to compare and contrast HR climate with organisational climate. This study employs an exploratory qualitative research design in which several in‐depth interviews were conducted with HR managers/directors. The findings suggest that although some dimensions of HR climate show similarities with those of organisational climate, there are significant differences. In addition, several dimensions of the HR climate found in this study reflect cultural characteristics of T urkey, specifically collectivism and paternalism. This extends knowledge of the concept of HR climate and shows that the construct may have dimensions that are culturally specific (particular) rather than universal.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.003
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
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 head0.048
GPT teacher head0.297
Teacher spread0.250 · 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 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

Citations11
Published2015
Admission routes1
Has abstractyes

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