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Record W2582935663 · doi:10.5539/jms.v7n1p19

Green Workplace Behaviour in Saudi Arabia: The Case of EnviroCo

2017· article· en· W2582935663 on OpenAlexvenueno aff
Nadia A. Abdulghaffar

Bibliographic record

VenueJournal of Management and Sustainability · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)SustainabilityGovernment (linguistics)BusinessWork (physics)Order (exchange)Public relationsMarketingEngineeringSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

In order to enhance sustainability in the workplace, recent research has focused on the practices which can promote employees’ green behaviour. However, there is little work that examines the extent to which companies use HRM practices to foster green bahaviour. This study has investigated this issue through a survey conducted in a government agency in Saudi Arabia. Overall, the findings suggest that senior managers are aware of the importance of green workplace behaviour and recognize that a certain number of HRM practices can promote and support this behaviour. However, these practices are not used effectively and senior managers can only marginally foster pro-environmental behaviour in their organization.

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)0.001
metaresearch head score (Gemma)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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