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Record W1968093176 · doi:10.1177/000765030104000202

Building Stakeholder Theory with a Decision Modeling Methodology

2001· article· en· W1968093176 on OpenAlex
Monika Winn

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

VenueBusiness & Society · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsConceptualizationStakeholderStakeholder analysisStakeholder theoryBusinessCorporate governanceManagement scienceProcess managementEnvironmental resource managementPublic relationsPolitical scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

This article focuses stakeholder theory on that critical juncture where stakeholder relationships and corporate policy decisions converge. A case study methodology is described that permits detailed analyses of multiple stakeholders’ objectives; it is suitable for studies of major corporate strategic decisions that are complex, controversial, involve multiple stakeholders, and require strategic trade-offs. The methodology is applied here to the dramatic decision by a Pacific Northwest forest company to phase out traditional clear-cut harvesting methods of old-growth forests. The study’s findings point to new research questions and have theoretical implications for a finer grained conceptualization of stakeholder groups, stakeholder objectives, and stakeholder issues.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.146
GPT teacher head0.315
Teacher spread0.169 · 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