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Record W3005645062 · doi:10.1111/csp2.176

From human invaders to problem bears: A media content analysis of grizzly bear conservation

2020· article· en· W3005645062 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueConservation Science and Practice · 2020
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsGovernment of AlbertaUniversity of Alberta
Fundersnot available
KeywordsUrsusGrizzly BearsFraming (construction)AnecdoteSurpriseAudience measurementRhetorical questionGeographyHistorySociologyPsychologySocial psychologyPolitical scienceLawArtArchaeology

Abstract

fetched live from OpenAlex

Abstract Across their North American range, grizzly bears ( Ursus arctos ) occupy a special place in human imagination, as icons of nature's rugged and raw power, to representations of safety risks and economic costs of living with carnivores. Different bear representations can also be found across news media, from controversial and sensational descriptions of attacks, tragic events and conflicts, to scientific accounts of conservation research. News media certainly has the power to pique curiosity, spark debate, or elicit emotional responses through framing and repetition of content. In turn, news stories can influence how people might interpret and internalize information about grizzly bears. Using media content analysis, we examined newsprint stories on grizzly bears across their North American range between 2000 and 2016, to understand message framing and attention cycle, as well as attitudinal expression and representative anecdote conveyed to the readership. We found that human–bear conflict stories are over‐reported compared to other narratives, where a single incidence garners more attention than a story about new scientific findings. We also found articles that included hunting frames largely originated in Alberta, likely due to the threatened species listing and hunting moratorium. Attitudinal expressions included ecological, negative or neutral, and moral sentiments toward bears. The most common representative anecdote conveyed to the readership reflected the dire state faced by grizzly bears. The bear eco‐gossip expressed in the articles we reviewed, which included clear protagonists and antagonists and the occasional man‐bites‐bear surprise, appears to be the diet of manufactured information fed to the public. Results of our study can help scientists and conservationists understand how news media portrays grizzly bears to the public and how this might influence public sentiment toward their conservation, but also identifies the roles that scientists, conservationists and journalists together can play in crafting effective, factual and engaging news stories about bears.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.603
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.272
GPT teacher head0.396
Teacher spread0.124 · 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