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Record W2017784926 · doi:10.1175/2011bams3219.1

Making the Climate a Part of the Human World

2011· article· en· W2017784926 on OpenAlexaff
Simon D. Donner

Bibliographic record

VenueBulletin of the American Meteorological Society · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsClimate changeScientific consensusOutreachEnvironmental ethicsClimate scienceScience communicationPublic opinionScientific evidenceGlobal warmingPolitical scienceSociologyEcologyEpistemologyScience educationLaw

Abstract

fetched live from OpenAlex

Doubts about the scientific evidence for anthropogenic climate change persist among the general public, particularly in North America, despite overwhelming consensus in the scientific community about the human influence on the climate system. The public uncertainty may be rooted in the belief, held by many cultures across the planet, that the climate is not directly influenced by people. The belief in divine control of weather and climate can, in some cases, be traced back to the development of agriculture and the early city-states. Drawing upon evidence from anthropology, theology, and communication studies, this article suggests that in many regions this deeply ingrained belief may limit public acceptance of the evidence for anthropogenic climate change. Successful climate change education and outreach programs should be designed to help overcome perceived conflict between climate science and long-held cultural beliefs, drawing upon lessons from communication and education regarding other potentially divisive subjects, such as evolution.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.019
Scholarly communication0.0080.007
Open science0.0010.004
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 head0.188
GPT teacher head0.336
Teacher spread0.148 · 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 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

Citations25
Published2011
Admission routes1
Has abstractyes

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