MétaCan
Menu
Back to cohort
Record W4401821909 · doi:10.1111/cars.12482

Building a new environmentalism: News media access and framing in Canada's environmental movement

2024· article· en· W4401821909 on OpenAlexafffundabout
Nicolas Graham, Joanna L. Robinson

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsYork UniversityUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council
KeywordsFraming (construction)EnvironmentalismEnvironmental justiceSocial movementTransformative learningPolitical scienceIndigenousEcological modernizationSociologyEnvironmental communicationNarrativePublic relationsEnvironmental ethicsMedia studiesLawEngineering

Abstract

fetched live from OpenAlex

This study provides a content and frame analysis of the news media advocacy of prominent environmental non-governmental organizations (ENGOs) in Canada. We find that these organizations have an important voice in shaping how climate change is framed in news media, but that ecological modernization frames and narratives, which avoid issues of power, conflict, and social-transformative change, are dominant. Core elements of this discourse are contested, however, as some ENGOs oppose the fossil sector, critique the shortcomings of proffered (technological) climate solutions, and call for muscular interventions aimed at energy transition. We also find that environmental justice frames - particularly those focused on Indigenous rights - are gaining traction, revealing a promising pathway of influence for ENGOs focused on climate justice.

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)0.007
metaresearch head score (Gemma)0.014
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: none
Teacher disagreement score0.096
Threshold uncertainty score0.693

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.008
Science and technology studies0.0280.033
Scholarly communication0.0240.006
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.256
Teacher spread0.198 · 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

Citations1
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Review of Sociology/Revue canadienne de sociologieSame topicRhetoric and Communication StudiesFrench-language works237,207