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Record W3215459489 · doi:10.5539/jsd.v15n1p1

Operationalizing Sustainable Development, Stakeholder Theory, Corporate Social Responsibility to Improve Community Engagement Outcomes

2021· article· en· W3215459489 on OpenAlexvenueno aff
Jerold Edson Ring

Bibliographic record

VenueJournal of Sustainable Development · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsOperationalizationStakeholder engagementCorporate social responsibilityStakeholderCreating shared valueTriple bottom linePublic relationsBusinessInterdependenceCommunity engagementSustainable businessValue (mathematics)SustainabilityMarketingSustainable developmentSociologyPolitical scienceEcology

Abstract

fetched live from OpenAlex

Businesses fail in the absence of an engagement strategy with stakeholders who influence and are influenced by a company’s business activity in communities where the company has a presence. A lack of understanding of the interdependency implicit in the company/community relationship, and the absence of new frameworks to encourage collaboration, has led increasingly to an inability to resolve conflicting views. An evolving approach is business participation in multisector collaborative watershed initiative partnerships. This qualitative multiple case study examines the perspectives of 22 participants of two watershed partnerships relating to corporate social responsibility (CSR), the Triple Bottom Line of sustainable development (TBL), and shared value. The study’s theoretical framework focuses on stakeholder theory integrated with the corporate imperatives of CSR, the TBL, and shared value. The research question is how these constructs might define an unexplored community engagement framework between the company, the community, and watershed initiatives. The research data suggests these factors are interrelated, and, when integrated into a strategy, define a Sustainable Community Engagement Framework that redefines the business case for engaging stakeholders to help resolve often conflicting views relating to the company’s business activity. The study outcomes are particularly relevant to academics, practitioners, business managers, and consultants engaged with high profile organizations such as chemical, petroleum and utility businesses whose presence may generate community concerns about their business activities, especially their environmental footprint.

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)0.022
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), 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 score0.411
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0000.001
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 head0.096
GPT teacher head0.294
Teacher spread0.198 · 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 designObservational
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

Citations8
Published2021
Admission routes1
Has abstractyes

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