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Record W4380874345 · doi:10.1002/9781119511847.ch17

Co‐management and Community‐Based Management

2023· other· en· W4380874345 on OpenAlexaffabout
Anthony Charles

Bibliographic record

Venuenot available
Typeother
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsStewardship (theology)IndigenousDevolution (biology)Community managementDecentralizationResource management (computing)Environmental resource managementCorporate governanceFisheries managementBusinessEnvironmental planningNatural resource managementCommunity-based managementManagement processPolitical scienceGeographyEcologyManagement systemEngineeringFishingNatural resourceComputer scienceOperations management

Abstract

fetched live from OpenAlex

This chapter focuses on two inter-related themes: co-management and community-based fisheries management. The development of self-regulated resource management approaches has been a remarkably widespread occurrence over history, by various civilisations, communities, and Indigenous populations around the world. Community-based co-management sometimes focuses on involving the community, as a whole, in management. This can be the case, for example, with Indigenous communities in Canada. Co-management is a development in fishery governance that draws on considerations of decentralisation and devolution in decision-making, and on recognition of the importance, for various reasons, of involving fishers in the management process. Community-based fisheries management is about the local community participating in, or even carrying out themselves, specific management activities. Community-based conservation and community science refer to environmental stewardship activities and knowledge-building efforts controlled and led by communities at the local level.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0080.014
Scholarly communication0.0090.007
Open science0.0020.012
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0250.002

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 head0.084
GPT teacher head0.415
Teacher spread0.332 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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