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Record W4398139440 · doi:10.3390/fishes9050187

Merits of Multi-Indicator Precautionary Approach Management in a Male-Only Crab Fishery

2024· article· en· W4398139440 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFishes · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsFisheryFisheries managementBusinessNatural resource economicsEnvironmental scienceEconomicsBiologyFishing

Abstract

fetched live from OpenAlex

Snow crab replaced groundfish fisheries as the primary focus of the Newfoundland and Labrador (NL) fishing industry in the mid-1990s. Over the past three decades, management philosophies in this male-only fishery have shifted from promoting industry expansion to promoting industry rationalization to implementing Precautionary Approach (PA) management. Until the mid-2010s, there were regionalized management strategies characterized by higher exploitation rates in northern than southern sub-stock units along the NL marine shelves. However, in the late 2010s, exploitation rates were permitted to elevate to high levels across the entire stock range in association with a large resource decline, and evidence of biological harm through fishing emerged in chronically depleted areas. In 2019, when stock and fishery productivity were near historical lows, a multi-indicator PA system was informally introduced into the management of the resource. This event coincided with anticipated improvements in stock and fishery performance. This paper examines the extent to which the multi-indicator PA management system, focused on the promotion of both biological protection and maximization of fishing efficiency, may have contributed to recent improvements in stock and fishery status. A suite of indicators from areas implementing PA guidance into management in 2019 prior to the formal adoption of the PA system in 2023 suggest the system has been highly beneficial in promoting rapid recovery and improving stock and fishery performance metrics to levels matching or exceeding historical levels under similar conditions. We discuss the capacity of the system to better safeguard biological aspects of resource and fisheries productivity moving forward under a scenario of an expectant resource decline.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.740
Threshold uncertainty score0.990

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.021
GPT teacher head0.256
Teacher spread0.234 · 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