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Record W2181313587

Convening Stakeholder Networks A New Way of Thinking, Being and Engaging

2005· article· en· W2181313587 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

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsStakeholderStakeholder engagementComplex adaptive systemSustainabilitySet (abstract data type)Knowledge managementStakeholder analysisBusinessPublic relationsStakeholder theoryPolitical scienceSociologyProcess managementComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

A growing number of companies are convening stakeholder networks to address complex sustainability and corporate responsibility issues. The role of network convenor is new for most companies, and it involves different ways of thinking, being and engaging beyond the more traditional approaches to managing bilateral stakeholder relationships. In this paper we describe how three companies established successful networks and then explore the mind-set, skill sets and engagement processes that are required to build and sustain multi-stakeholder networks. The paper draws on theory and research related to complex adaptive systems, collective learning and whole-system change. l Stakeholder l Engagement l Networks l Collective learning l Whole system change

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.729
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.189
GPT teacher head0.367
Teacher spread0.178 · 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

Quick stats

Citations64
Published2005
Admission routes1
Has abstractyes

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