Exploring Reasons for Varying Support for the Status Quo among Ontario’s Moose Hunters
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.
Bibliographic record
Abstract
Strong public support for the status quo often occurs when wildlife managers propose changes to regulations and policies. We illustrated that this support is highly variable for three contexts (vague, general, and specific) that involved potentially more restrictive regulations for hunting moose (Alces alces) in northeastern Ontario, Canada. Status quo support was highest (88%) when hunters were questioned with a vague context (i.e., do you support more restrictive regulations to hunt for moose). This support was lowest (19%) when hunters were provided with detailed descriptions of restrictive options with tradeoff information about benefits of adopting new regulations (i.e., the specific context). We concluded that loss aversion and omission biases were primarily responsible for the observed variability in status quo support. We also suggest that initially strong support for the status quo might crumble when people better understand non–status quo options.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it