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Record W2550616871 · doi:10.5539/ibr.v9n12p153

Analytical and Theoretical Perspectives on Green Human Resource Management: A Simplified Underpinning

2016· article· en· W2550616871 on OpenAlexvenueno aff
Arul Arulrajah, H. H. D. N. P. Opatha

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsUnderpinningWrightHuman resource managementField (mathematics)Knowledge managementManagement scienceResource (disambiguation)BusinessComputer scienceEngineeringMathematics

Abstract

fetched live from OpenAlex

<p>This review paper creates strong analytical and theoretical frameworks for green human resource management (GHRM) literature. As green HRM is an emerging field of study it requires strong analytical and theoretical frameworks to underpin the valuable knowledge obtained by the scholars through systematic research works in this field. A review of the literature shows that strong analytical and theoretical frameworks for green HRM has yet to be emerged. Accordingly, the objective of this paper is to fill this knowledge gap considerably. This paper organizes the existing literature on the bases of ‘Analytical HRM Framework’ of Boxall, Purcell, & Wright (2007) and other relevant organisational theories. Ultimately this paper establishes a strong link between existing literature in green HRM and organizational theories.</p>

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.038
GPT teacher head0.338
Teacher spread0.301 · 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.

Study designTheoretical or conceptual
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

Citations103
Published2016
Admission routes1
Has abstractyes

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