MétaCan
Menu
Back to cohort
Record W4414261772 · doi:10.1111/fme.70010

Angler Heterogeneity in Newfoundland and Labrador, Canada: Insights From Nearly Three Decades (1994–2022) of Atlantic Salmon Angler License and Activity Records

2025· article· en· W4414261772 on OpenAlexaffabout
Travis E. Van Leeuwen, Michelle G. Fitzsimmons, J. Brian Dempson, C White, Mark Young, Donald Keefe, Isabelle Schmelzer, Nicholas I. Kelly, Craig F. Purchase, Blair Adams, David Côté

Bibliographic record

VenueFisheries Management and Ecology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMemorial University of NewfoundlandGovernment of Newfoundland and LabradorFisheries and Oceans Canada
Fundersnot available
KeywordsLicenseDemographicsRecreationRecreational fishingFisheries managementCatch and release

Abstract

fetched live from OpenAlex

ABSTRACT Angler demographics and motivations are an important consideration to successful fisheries management. We examined 29 years of angler license and activity records from the recreational Atlantic salmon fishery in Newfoundland and Labrador, Canada to: (1) provide a contemporary evaluation of angler demographic trends; (2) evaluate age and regional differences between anglers who prioritized retention versus catch‐and‐release; and (3) discuss how various management and COVID restrictions affected angler participation and activity. Resident license holders made up 91.3% of total licenses purchased. The average age of license holders increased from 39 years of age in 1994 to 54 years of age in 2022, with 6–20 year olds making up < 1% of license holders since 2019. Overall, 24.2% of anglers prioritized only retaining salmon, and 2.2% only releasing salmon, with anglers from rural areas more likely than those from urban areas to only retain salmon. Following a tightening of warm water thresholds for river closure and reductions in catch‐and‐release and retention limits, including a mid‐season ban on retention in 2018, the percentage of anglers who prioritized only releasing salmon increased. In contrast, the percentage of anglers who prioritized only retaining salmon decreased. Results provide a rare insight into angler spatial and temporal demographics and motivations that can be used to help guide management options that are likely to be supported by local communities and stakeholders.

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 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 score0.685
Threshold uncertainty score0.694

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 science0.0000.001
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 head0.007
GPT teacher head0.192
Teacher spread0.185 · 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 teacher head, 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueFisheries Management and EcologySame topicFish Ecology and Management StudiesFrench-language works237,207