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Record W4286615919 · doi:10.1371/journal.pclm.0000048

On the acceptance of intergenerational climate legacies: A comparison of Canada and Japan

2022· article· en· W4286615919 on OpenAlex
Kyoko Adachi, Hadi Dowlatabadi, Jiaying Zhao

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePLOS Climate · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaCanada Research ChairsCarnegie Mellon UniversityNational Science Foundation
KeywordsNegotiationClimate justiceClimate changeCompensation (psychology)Economic JusticeInheritance (genetic algorithm)IntentionalityWillingness to acceptPolitical scienceSettlement (finance)Social psychologyEnvironmental ethicsSociologyPsychologyWillingness to payEconomicsLawEcology

Abstract

fetched live from OpenAlex

Intergenerational climate justice negotiations often flounder on three questions: What was the outcome on climate change? Was it intentional? Why should the current generation pay for the misdeeds of previous generations? In this research, participants from Japan and Canada rated their willingness to accept intergenerational climate legacies and the responsibilities these legacies entail; judged the importance of intent and outcome associated with creating these legacies; and rated their willingness to compensate those negatively impacted by previous generations. The study found: a) while outcome was important, intent did not matter; b) Canadians were more likely to accept an inheritance and c) more likely to equivocate, in acceptance, if it entailed obligations than the Japanese; d) among those who accepted the inheritance, Japanese were more generous in settlement of previous generation’s obligations; e) lower-income, non-Judeo-Christian participants were systematically fairer than others; and f) the resistance to compensation for past generations’ actions was diminished with the awareness about the broad scope of intergenerational climate legacies that the current generation enjoyed. Our findings highlight the influences of culture and historic awareness on accepting climate responsibilities for actions of previous generations and willingness to provide compensation. The findings also support abandoning the debate on intentionality.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.307
Teacher spread0.266 · 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