Operationalizing Sustainable Development, Stakeholder Theory, Corporate Social Responsibility to Improve Community Engagement Outcomes
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".