MétaCan
Menu
Back to cohort
Record W4417483805 · doi:10.3389/fclim.2025.1669144

Carbon emissions and subjective well-being in Blue Zone Ikaria and Athens, Greece

2025· article· en· W4417483805 on OpenAlexafffund
Jade Radke, Stella Argentopoulos, Jiaying Zhao

Bibliographic record

VenueFrontiers in Climate · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of British Columbia
KeywordsGreenhouse gasConsumption (sociology)ClothingCarbon fibersExploratory researchClimate change

Abstract

fetched live from OpenAlex

Reducing carbon emissions has become largely synonymous with personal sacrifice that can decrease subjective well-being (i.e., happiness, life satisfaction). However, a growing body of research suggests that pro-environmental behavior is positively associated with subjective well-being. To further examine this relationship, this exploratory study examined individual carbon emissions and subjective well-being in Blue Zone Ikaria, Greece, using Athens as a comparison site. Structured interviews and questionnaires with 46 participants (22 in Ikaria, 24 in Athens) revealed that Icarian participants reported higher mental well-being and lower carbon emissions from air travel and clothing consumption than Athenian participants. Icarian participants were also more likely to grow their own food and identify as part of a tight-knit community. These findings suggest that community-focused lifestyles may promote mental well-being while reducing carbon emissions. Future research with larger, more representative samples and objective emissions data is needed to further explore this relationship in Ikaria and other non-WEIRD (Western, Educated, Industrialized, Rich, Democratic) societies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.441

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 studies0.0000.000
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 head0.003
GPT teacher head0.232
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in ClimateSame topicEnvironmental Education and SustainabilityFrench-language works237,207