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Record W1494071200 · doi:10.1111/deci.12085

Socially Responsible Practices: An Exploratory Study on Scale Development using Stakeholder Theory

2014· article· en· W1494071200 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

VenueDecision Sciences · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsWestern University
Fundersnot available
KeywordsStakeholderConstruct (python library)BusinessExploratory researchStakeholder theoryKnowledge managementSet (abstract data type)Stakeholder analysisCorporate social responsibilityScale (ratio)Spillover effectMarketingProcess managementPublic relationsComputer scienceSociologyEconomicsMicroeconomicsPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT Socially responsible practices of firms have evolved into an important area of research in operations management; however, it remains challenging to identify specific scales that capture multiple dimensions of such social practices. In this exploratory study, we use stakeholder theory to develop new multi‐item measurement scales linked to multiple groups (i.e., internal, supplier, customer, and community stakeholders). Furthermore, we empirically test a higher order multidimensional construct that collectively assesses the socially responsible practices of a firm. Using these stakeholder‐derived constructs as taxons in a cluster analysis, we identify important patterns in the way that multiple groups of stakeholders are engaged. Finally, we demonstrate that the set of social practices are complementary and concentrating on one group can yield spillover effects to other specific stakeholder groups.

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)0.026
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.003
Open science0.0010.000
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 head0.304
GPT teacher head0.396
Teacher spread0.092 · 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