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Record W2511838043 · doi:10.5296/ber.v6i2.9865

Scale Development and Operationalization of Social Responsibility Constructs: An ISO 26000 Context

2016· article· en· W2511838043 on OpenAlexaff
Pui‐Sze Chow, Ailie K.Y. Tang, Amy C.Y. Yip

Bibliographic record

VenueBusiness and Economic Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsCentennial College
Fundersnot available
KeywordsOperationalizationSocial responsibilityScale (ratio)Mainland ChinaCorporate social responsibilityContext (archaeology)BusinessAccountingChinaPublic relationsPolitical scienceGeography

Abstract

fetched live from OpenAlex

ISO 26000 is one of those prevailing guidelines on social responsibility adopted by practitioners. Despite its growing embracement, the dimensions of ISO 26000 have not been empirically operationalized. The lack of validated scales limits its compatibility in real-life practices as well as academic research on the standard. Adopting quantitative and qualitative methodology, the multidimensional scale of ISO 26000 is first operationalized through a questionnaire survey with 286 organizations in Hong Kong. The measurement items are then triangulated with industrial evidence garnered from in-depth interviews with seven organizations comprising two listed companies, two private companies, and three non-governmental organizations with operations in Hong Kong, Macau, Mainland China, Asia and the Middle East. Our measurement scale contributes to future studies of ISO 26000 in the corporate social responsibility literature. The validated scale will also be a handy guide for aligning social responsibility with the practical context and strategic implantation.

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)0.028
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.061
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.005
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.003
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 head0.049
GPT teacher head0.305
Teacher spread0.256 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations5
Published2016
Admission routes1
Has abstractyes

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