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Record W4200363941 · doi:10.1177/00027642211056258

Morality, Emotions, and the Ideal Environmentalist: Toward A Conceptual Framework for Understanding Political Polarization

2021· article· en· W4200363941 on OpenAlexaff
Emily Huddart Kennedy, Parker Muzzerall

Bibliographic record

VenueAmerican Behavioral Scientist · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPoliticsIdeal (ethics)MoralityPolarization (electrochemistry)Social psychologySociologyEnvironmental ethicsEnvironmentalismPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Americans are politically polarized in their views on environmental protection, and scholars have identified structural and cultural drivers of this polarity. Missing from these theories is a consideration of the emotional dynamics at play in environmentally relevant interactions between liberals and conservatives. Based on analyses of in-depth interviews conducted with 63 politically and socioeconomically diverse residents of four communities in Washington State, we find evidence of important common ground across the political spectrum. Our participants voice support and respect for environmental protection and convey a shared image of an ideal environmentalist: a conscious, caring, and committed individual who seeks to reduce their personal environmental impact. We see political differences arise when our participants evaluate their own relationship with the environment against this ideal environmentalist. Liberals are more likely to align with or admire the ideal environmentalist and conservatives are more likely to challenge or denigrate the ideal. Emotions and competing claims for moral worth, we suggest, play a role in making these political differences polarizing.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
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 studies0.0010.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.445
GPT teacher head0.474
Teacher spread0.029 · 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 designTheoretical or conceptual
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

Citations16
Published2021
Admission routes1
Has abstractyes

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