MétaCan
Menu
Back to cohort
Record W2508704520 · doi:10.1080/10871209.2016.1214886

Exploring Reasons for Varying Support for the Status Quo among Ontario’s Moose Hunters

2016· article· en· W2508704520 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHuman Dimensions of Wildlife · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsMinistry of Natural Resources and Forestry
FundersOntario Ministry of Natural Resources and Forestry
KeywordsStatus quoContext (archaeology)Status quo biasPublic supportWildlifeBusinessPolitical sciencePublic economicsGeographyEcologyEconomicsLawBiology

Abstract

fetched live from OpenAlex

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.

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.

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 score0.082
Threshold uncertainty score0.392

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 science0.0000.000
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 head0.236
GPT teacher head0.252
Teacher spread0.015 · 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