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Record W2164909164 · doi:10.1177/0021886301374005

Toward Common Ground and Action on Repetitive Strain Injuries

2001· article· en· W2164909164 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

VenueThe Journal of Applied Behavioral Science · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsInstitute for Work & Health
Fundersnot available
KeywordsCommon groundAction (physics)StakeholderCLARITYCitizen journalismPublic relationsParticipatory action researchPsychologyKnowledge managementPolitical scienceSociologySocial psychologyComputer scienceLaw

Abstract

fetched live from OpenAlex

Numerous participatory approaches to action on complex issues have emerged in recent years. One approach, the Future Search conference, is said to build a shared vision and rapid action by diverse stakeholders. This article reports on a detailed qualitative analysis of a Future Search conference on repetitive strain injuries, an ambiguous, conflictridden, and systemic problem. The Future Search encouraged the expression of diverse perspectives and mapped a certain domain of common ground. It stimulated various kinds of action, enhanced stakeholder involvement and awareness, and increased commitment to multistakeholder dialogue and action. Several weaknesses of the Future Search model are identified. Specifically, this study suggests the need for more participant clarity about what is expected, a more solid framework to support follow-up action, greater explicitness about what constitutes common ground, and more time for common-ground building and action planning.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.053
GPT teacher head0.311
Teacher spread0.258 · 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