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Record W2914058545 · doi:10.1071/wr18035

Retaining change in attitudes and emotions toward coyotes using experiential education

2019· article· en· W2914058545 on OpenAlexaff
Carly C. Sponarski, Jerry J. Vaske, Alistair J. Bath, TA Loeffler

Bibliographic record

VenueWildlife Research · 2019
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWildlifeExperiential learningContext (archaeology)PerceptionPsychologyTest (biology)Experiential educationWildlife conservationApplied psychologyRisk perceptionMedical educationSocial psychologyEcologyMedicineGeographyPedagogy

Abstract

fetched live from OpenAlex

Context Education programs concerning wildlife conservation and safety typically include the biology of the wildlife species and public safety information. Information retention using traditional means such as signs, pamphlets and static presentations have been shown to be minimally effective at changing attitudes and behaviour when it comes to human–wildlife interactions. Aims An experiential education program with interactive modules was designed to support information retention in participants. On the basis of previous research, a targeted experiential education program focusing on perceptions of risk and preventative behaviours was produced to increase people’s comfort level when in coyote habitat. Methods Pre-, post- and retention-test questionnaires were used to study differences in attitudes and risk perception instantly following (post-test) as well as 1 year after participating in the program (retention test). Key results Overall, the program had significant positive effects on participants’ attitudes, and significant decreases in their overall perception of risk in terms of potential interaction with coyotes. These positive effects were observed instantly and 1 year after participants were surveyed. Conclusions Targeted and interactive educative experiences can have impacts on participants’ perceptions over the long term. This technique might be useful when dealing with human–wildlife interactions. Implications Designing targeted educative experiences for people may also support lasting positive change in human–wildlife interactions.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.300
GPT teacher head0.503
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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