Online hunting forums identify achievement as prominent among multiple satisfactions
Bibliographic record
Abstract
ABSTRACT Understanding hunter satisfactions can lead to improved wildlife management policy and practice. Whereas previous work has suggested that hunters often seek multiple satisfactions (achievement, affiliation, appreciation), little is known about how satisfactions might vary with target species. Additionally, past research has mostly gathered data using interviews and surveys, which might limit scope as well as introduce strategic bias for potentially provocative subjects such as hunting. To address these gaps, we analyzed data from online hunting forums, which provide an open‐access source of peer‐to‐peer discussion that is geographically and taxonomically broad. We used directed qualitative content analysis to analyze hunting narratives for satisfactions by coding 2,864 phrases across 455 hunting “stories,” and compared patterns of dominant (most frequent) and multiple satisfactions between target species type (ungulates and carnivores) using forums from 3 regions: British Columbia, Canada; Texas, USA; and North America‐wide. We found that achievement was the dominant satisfaction in 81% of ungulate and 86% of carnivore stories. Appreciation was nearly absent as a dominant satisfaction in carnivore stories. We found that 62% of ungulate and 53% of carnivore stories had multiple satisfactions present, indicating that appreciation and affiliation play important secondary satisfaction roles even when achievement is dominant. If these data are broadly representative of hunters on a larger scale, management policy instruments that ignore achievement may not evoke change in hunter behavior, particularly involving carnivore target species. Despite limitations associated with online forums (e.g., nonrepresentative of all hunters), they provide a new and valuable resource for wildlife management research. © 2017 The Authors. Wildlife Society Bulletin published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".