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Public Preference for Endemism over Other Conservation‐Related Species Attributes

2009· article· en· W2084116337 on OpenAlexaffabout
Emily Meuser, Howard W. Harshaw, Arne Ø. Mooers

Bibliographic record

VenueConservation Biology · 2009
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsEndemismPreferenceNature ConservationGeographyBiodiversity conservationConservation biologyEcologyBiologyBiodiversityMathematicsStatistics

Abstract

fetched live from OpenAlex

Public preferences are likely to play an important role in prioritizing species at risk for conservation. We conducted a survey of British Columbians (Canada) (n =555, r =73%) to examine how the public ranks a species' attributes (rather than named species) with respect to conservation priority. Endemism, defined as species only or mainly occurring in British Columbia or species occurring in British Columbia and nowhere else in Canada, was considered the most important among the measured attributes. This preference was strongest among men and among respondents who had completed postsecondary education. The preference for endemism is generally consistent with science-based federal listings of British Columbian species. This congruence between listing and public opinion is welcome if such congruence is considered important. We suggest that investigating how much the public values species' attributes, as opposed to named species, provides a more efficient way of incorporating public opinion into policies on species at risk, especially if large numbers of species must be ranked for conservation priority.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.139
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.249
GPT teacher head0.344
Teacher spread0.095 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations58
Published2009
Admission routes2
Has abstractyes

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