MétaCan
Menu
Back to cohort
Record W2067416431 · doi:10.1080/10871200304308

Attitudinal and Normative Influences on Support for Hunting as a Wildlife Management Strategy

2003· article· en· W2067416431 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.

Bibliographic record

VenueHuman Dimensions of Wildlife · 2003
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsWildlifeNormativeWildlife managementGovernment (linguistics)Wildlife conservationEnvironmental resource managementVariety (cybernetics)PsychologyTheory of reasoned actionGeographyBusinessEnvironmental planningPublic relationsSocial psychologyPolitical scienceEcologyEconomics

Abstract

fetched live from OpenAlex

Hunting as a wildlife management tool has come under increasing attack by antihunting organizations. This has resulted in increased concern by fish and wildlife agencies across North America, many of whom fear that the scientific management of wildlife is in danger due to the influence of an uninformed public. A province-wide survey based upon the Theory of Reasoned Action framework was conducted to examine residents' attitudes toward hunting in a variety of contexts. Results from over 1,300 respondents indicated support for hunting as wildlife management, for habitat preservation, and to maintain healthy animal populations. Attitudinal and normative influences were also examined based on level of intention to support hunting. Results of this research provide information regarding the underlying beliefs and referent groups likely to influence individual's support of hunting, which can then be used by government and others charged with the scientific management of wildlife to communicate successfully the role and significance of hunting in this regard.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score0.467

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 head0.058
GPT teacher head0.355
Teacher spread0.297 · 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