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Record W2993177240 · doi:10.1108/jgr-03-2019-0033

Good neighbor or good employer?

2019· article· en· W2993177240 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

VenueJournal of Global Responsibility · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsCarleton University
Fundersnot available
KeywordsCorporate social responsibilityOperationalizationReputationOriginalityStakeholderLeverage (statistics)BusinessStakeholder theoryStatus quoPublic relationsMarketingStakeholder engagementInstitutional theoryAccountingQualitative researchEconomicsPolitical scienceSociologyManagementComputer science

Abstract

fetched live from OpenAlex

Purpose This study aims to test Mattingly and Berman’s (2006) taxonomy of social actions and develops divergent expectations for corporate social responsibility (CSR) dimensions directed toward institutional and technical stakeholders, with an aim to determine when CSR directed to different stakeholders is most likely to improve corporate reputation. Design/methodology/approach A longitudinal sample of 285 major US corporations was used to quantitatively test the hypotheses. Data was sourced from KLD, Osiris and Fortune MAC. Findings Strengths in CSR and actions directed toward technical stakeholders influence corporate reputation in a more profound way, when compared to those directed toward institutional stakeholders. Contrary to the authors’ prediction, institutional concerns do not demonstrate a significant growth or reduction over the five-year period. Research limitations/implications This study provides a longitudinal test of Mattingly and Berman’s (2006) taxonomy of CSR actions and makes an important methodological contribution by operationalizing CSR not as a continuum from strengths to concerns, rather as two distinct constructs. Practical implications Management practice can benefit from a more fine-grained approach to stakeholder expectations and reputation outcomes. The results of this study leverage relevant stakeholder impact while allowing firms to appreciate the change in CSR actions and to measure it accordingly, such that the undesirable status quo that leads to potential loss in reputation growth can be avoided. Social implications As organizations explore ways to effectively engage stakeholders for mutual benefit, this research shows how firms can have a positive impact. Originality/value This study tests and extends theory through an integrated lens, built on the stakeholder and resource dependence theories, while directing management attention to the broader reputational outcomes of targeted CSR initiatives. It provides justification for CSR investments over time.

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)0.006
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.024
GPT teacher head0.292
Teacher spread0.268 · 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