MétaCan
Menu
Back to cohort
Record W2914555011 · doi:10.1080/17524032.2018.1557726

Canadian Weathercasters’ Current and Potential Role as Climate Change Communicators

2019· article· en· W2914555011 on OpenAlexaffabout
Bronwyn McIlroy‐Young, Jason Thistlethwaite

Bibliographic record

VenueEnvironmental Communication · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of WaterlooUniversity of British Columbia
Fundersnot available
KeywordsClimate changeSituatedPublic engagementPolitical sciencePolitical economy of climate changeAction (physics)Environmental resource managementGeographyPublic relationsEnvironmental planningEnvironmental scienceEcologyComputer science

Abstract

fetched live from OpenAlex

Climatologists worldwide are calling for urgent action to manage climate change, but public engagement remains a significant challenge. This lack of engagement is often attributed to psychological distance: climate change is perceived as something happening far away, to other people, or in a hypothetical future. TV weathercasters are ideally situated to communicate the geographically and temporally proximate impacts of climate change and increase public engagement. This study explores the status of climate change reporting amongst weathercasters in Canada, where no such research has been conducted. The respondents suggested that many, but not all, weathercasters are engaged with climate change and interested in presenting local, climate-related content; however, their on-air climate change communication behavior is highly limited. This analysis builds on research conducted with American weather broadcaster by indicating that Canadian weathercasters share their potential as effective climate change communicators, but are highly uncertain about their capacity to support this role.

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0150.004
Scholarly communication0.0070.003
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.133
GPT teacher head0.355
Teacher spread0.222 · 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 designQualitative
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

Citations7
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueEnvironmental CommunicationSame topicClimate Change Communication and PerceptionFrench-language works237,207