Angler Heterogeneity in Newfoundland and Labrador, Canada: Insights From Nearly Three Decades (1994–2022) of Atlantic Salmon Angler License and Activity Records
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".