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Record W2156321482 · doi:10.18352/ijc.148

Cumulative effects, creeping enclosure, and the marine commons of New Jersey

2010· article· en· W2156321482 on OpenAlexaff
Grant Murray, Teresa R. Johnson, Bonnie J. McCay, Mike Danko, Kevin St. Martin, Satsuki Takahashi

Bibliographic record

VenueInternational Journal of the Commons · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsCommonsFisheryEnclosureBusinessCorporatizationPolitical scienceEngineeringLawBiology

Abstract

fetched live from OpenAlex

In response to declining fish stocks and increased societal concern, the marine ‘commons’ of New Jersey is no longer freely available to commercial and recreational fisheries. We discuss the concept of ‘creeping’ enclosure in relation to New Jersey’s marine fisheries and suggest that reduced access can be a cumulative process and function of multiple events and processes and need not be the result of a single regulatory moment. We begin with a short review of the ‘expected’ effects of enclosure, including loss of flexibility, erosion of community, proletarianization of fishermen, and corporatization of the fishery. We then present some findings of our research and discuss how the signs of enclosure are visible in fisheries that do not feature explicitly privatized property or access rights. We rely on an oral history approach and the rich detail that emerges from attention to the lived experiences of fish harvesters to provide a framework for understanding the range of cumulative effects that have resulted from this process of creeping enclosure. We conclude with a discussion of how the gradual process of enclosure has affected the flows of information between the bio-physical environment and fish harvesters, managers and scientists by reducing both participation in fisheries and the accumulation of knowledge itself.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.201
Threshold uncertainty score0.400

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.336
Teacher spread0.314 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations52
Published2010
Admission routes1
Has abstractyes

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