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Good news, bad news: global fisheries discards are declining, but so are total catches

2005· article· en· W2141124005 on OpenAlexaff
Dirk Zeller, Daniel Pauly

Bibliographic record

VenueFish and Fisheries · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British Columbia
FundersPew Charitable Trusts
KeywordsDiscardsFisheryFishingFish <Actinopterygii>Value (mathematics)Political scienceBiologyComputer science

Abstract

fetched live from OpenAlex

Ghoti papers Ghoti aims to serve as a forum for stimulating and pertinent ideas. Ghoti publishes succinct commentary and opinion that addresses important areas in fish and fisheries science. Ghoti contributions will be innovative and have a perspective that may lead to fresh and productive insight of concepts, issues and research agendas. All Ghoti contributions will be selected by the editors and peer reviewed. Etymology of Ghoti George Bernard Shaw (1856‐1950), polymath, playwright, Nobel prize winner, and the most prolific letter writer in history, was an advocate of English spelling reform. He was reportedly fond of pointing out its absurdities by proving that ‘fish’ could be spelt ‘ghoti’. That is: ‘gh’ as in ‘rough’, ‘o’ as in ‘women’ and ‘ti’ as in palatial. Abstract During fishing operations, fish are often caught that were not targeted. When the species in question are of low value, or protected, this ‘by‐catch’ is often thrown overboard as ‘discards’, the retained part of the catch constituting the landings. The amounts of fish discarded are generally highly area‐ and gear‐specific, but can be high; for example, discards in tropical shrimp trawl fisheries may be one order of magnitude higher than the retained catch. The latest analysis undertaken by the Food and Agriculture Organization of the United Nations suggests that global discards have declined in recent years, indicating that wastage is being reduced in global fisheries operations. By all accounts, reducing waste is a good thing, and hence good news. Nevertheless, if one considers this decline in discards in conjunction with the reported decline in global fisheries landings over the last decade, it becomes evident that total global fisheries catches (consisting of landings plus discards) might have declined at a substantially steeper rate than previously thought. This could be bad news, if it is indicative of declining total availability of fish. While acknowledging the high uncertainty in both discard and landings data at the global scale through time, the present observation may serve as an urgent reminder that global fisheries may be in more trouble than we thought previously.

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)0.020
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: none
Teacher disagreement score0.024
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0020.004
Scholarly communication0.0090.010
Open science0.0010.003
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0240.011

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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

Citations153
Published2005
Admission routes1
Has abstractyes

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