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Record W2171549343 · doi:10.5751/es-01431-110145

From Community-Based Resource Management to Complex Systems: The Scale Issue and Marine Commons

2006· article· en· W2171549343 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEcology and Society · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCommonsEnvironmental resource managementResource management (computing)Scale (ratio)BusinessResource (disambiguation)Natural resource managementEnvironmental planningComputer scienceGeographyEcologyEnvironmental scienceNatural resource

Abstract

fetched live from OpenAlex

Most research in the area of common and common-pool resources in the past two or three decades sought the simplicity of community-based resource management cases to develop theory. This was done mainly because of the relative ease of observing processes of self-governance in simple cases, but it raises questions related to scale. To what extent can the findings of small-scale, community-based commons be scaled up to generalize about regional and global commons? Even though some of the principles from community-based studies are likely to be relevant across scale, new and different principles may also come into play at different levels. The study of cross-level institutions such as institutions of co-management, provides ways to approach scale-related questions and deal with linkages in complex adaptive systems. Looking beyond self-governance, community-based resource management needs to deal with multiple levels of governance and external drivers of change, as illustrated in this paper with examples of marine commons.

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)0.000
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 score0.197
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.012
GPT teacher head0.199
Teacher spread0.187 · 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