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Record W7106105636 · doi:10.25316/ir-20519

Seeking Common Ground: An Exploration of Conflicting Views on Climate Change in Saskatchewan

2025· dissertation· en· W7106105636 on OpenAlexaboutno aff

Bibliographic record

VenueVIUSpace (Vancouver Island University Library) · 2025
Typedissertation
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeTransformative learningCommon groundCollective actionPoliticsIdeologyPolitical economy of climate changeRhetoricClimate justice

Abstract

fetched live from OpenAlex

In the province of Saskatchewan, political rhetoric and deep economic dependency on non-renewable resources have contributed to a divided public opinion of both the presence and urgency of climate change. This clash of opposing views and beliefs on climate change has fostered an us-versus-them mentality that obfuscates efforts to effectively communicate both the impacts of climate change and the potential solutions. Narratives advanced by environmentally conscious individuals and organizations in Saskatchewan often fail to resonate across the ideological divide, which limits the efficacy of cultivating pro-environmental attitudes and behaviours across the province. To foster a shared pro-environmental outcome, new ways of thinking are needed to bridge the diverse meanings, experiences, and contexts that shape how people understand and respond to climate change. This study explores the potential for common ground among Saskatchewan people who hold conflicting views and beliefs about climate change and considers how this could support both the reduction of polarization and the creation of equitable pathways for meaningful climate action, in ways that honour a multitude of lived experiences. Central findings reveal tensions in how participants perceive climate challenges and possible responses. However, the presence of underlying shared values—such as sense of place, a desire for personal and economic wellbeing, and strong family and community ties—suggests meaningful opportunities to strategically frame climate change communication in ways that bridge divides and encourage transformative collective action in the land of the living skies.

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)0.003
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 score0.175
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0250.011
Scholarly communication0.0080.003
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.180
GPT teacher head0.364
Teacher spread0.184 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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