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Record W1921317864 · doi:10.1080/08941920.2015.1020976

Eliciting Values and Principles of Fishery Stakeholders in South Korea: A Methodological Exploration

2015· article· en· W1921317864 on OpenAlex
Andrew M. Song, Ratana Chuenpagdee

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

VenueSociety & Natural Resources · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsStakeholdersortCorporate governanceResource (disambiguation)Natural resourceProcess (computing)Value (mathematics)SortingExploratory researchSalientEnvironmental resource managementEmpirical researchBusinessManagement scienceSociologyKnowledge managementComputer sciencePolitical sciencePublic relationsEconomicsSocial scienceManagementEpistemologyLaw

Abstract

fetched live from OpenAlex

Growing importance of the governance concept has meant consideration and incorporation of wide interests and worldviews of various stakeholder groups. Yet this trend may also intensify complexity, as more diverse values and principles are represented. We design a simple and interactive survey-based technique to elicit and examine stakeholder values and principles in an effort to help guide natural resource governance. This exploratory approach, called “P+ sort” to recognize its methodological foundation on both pile sort and Q sort methods, utilizes a semistructured sorting procedure with verbal questions to capture both quantitative and qualitative data. An empirical application of P+ sort was conducted in South Korean fisheries, which were undergoing a governance reform. Results show promising utilities of P+ sort for identifying value priorities and salient principles of stakeholder groups, examining the convergence as well as notable differences in these elements, and providing policy-relevant input into the natural resource governance process.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.507
GPT teacher head0.294
Teacher spread0.212 · 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