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Record W4403321421 · doi:10.1038/s44168-024-00169-3

Barriers and pathways to climate action among nature lovers

2024· article· en· W4403321421 on OpenAlexafffundabout
Lisa Y. Seiler

Bibliographic record

Venuenpj Climate Action · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsYork University
FundersYork University
KeywordsAction (physics)Climate changePsychologyGeographyEcologyBiology

Abstract

fetched live from OpenAlex

One barrier to action on climate change is not talking about it. The majority of residents of the United States and Canada are concerned about climate change 1 , 2 but are reluctant to discuss it with family and friends 1 , 3 , 4 , 5 . Finding opportunities to promote conversation about climate change within existing social circles would help to increase the acceptability of climate actions 6 , 7 . In this study, 32 semi-structured interviews were held with representatives of nature-related organisations in Ontario, Canada, to ascertain how they perceive climate change. Most interviewees noticed local effects of climate change and were either Alarmed or Concerned about climate change, referencing Global Warming’s Six Americas 3 . Many worried about their chosen activity or their offspring. This suggests that nature lovers, who might distance themselves from the environmental movement 8 , could be amenable to discussing and acting on climate change. This article adds to the literature on laypeople’s understanding of climate change 9 , 10 , 11 .

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.262
GPT teacher head0.449
Teacher spread0.187 · 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 teacher head, not a consensus.

Study designNot applicable
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

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