MétaCan
Menu
Back to cohort
Record W4241168761 · doi:10.31235/osf.io/kzm5u

Disrupting the Complacency: Disaster Experience and Emergent Environmentalism

2021· preprint· en· W4241168761 on OpenAlexaboutno aff
Timothy J. Haney

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmentalismDenialFlood mythClimate changeEnvironmental changePolitical scienceNatural disasterEnvironmental ethicsPsychologyGeographyPoliticsEcologyLaw

Abstract

fetched live from OpenAlex

As climate change intensifies, scholars are beginning to ask whether first-hand experience in disaster will cause often-complacent people to develop greater environmental concern and engage in more pro-environmental behaviors. Will the disruption caused by experiencing an environmental disaster be enough to motivate residents to change their values and behaviors? This study answers that question by analyzing qualitative interview data collected from 40 residents of Calgary, Alberta, who survived the devastating and costly 2013 Southern Alberta Flood. Despite normally high levels of climate change denial and complacency, findings indicate that the flood prompted residents to concern themselves more with climate change and the climate crisis, and to begin adopting many household-level pro-environmental behaviors. The findings also point to important gender differences in both environmental concern and pro-environmental behaviors. Thus, the article establishes a social-psychological process of attitudinal and behavioral change, allowing us to better understand how jarring environmental events rupture complacency.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.049
GPT teacher head0.351
Teacher spread0.302 · 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 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicRisk Perception and ManagementFrench-language works237,207