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Record W7124739870 · doi:10.29344/07180772.45.4060

Willingness to adopt sustainable behaviors: A comparison among Spanish, Italian, and Mexican university members

2025· article· W7124739870 on OpenAlexaff
Bárbara Badanta, María Borrego- Marín, Lorena Tarriño-Concejero, Claudia Alejandra Corpus-Espinosa, Donatella Alessia-Lopopolo, Giancarlo Luchetti, Rocío De Diego-Cordero

Bibliographic record

VenueForo Educacional · 2025
Typearticle
Language
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsCanadian Physiotherapy Association
FundersUniversidad de Sevilla
KeywordsSustainabilityHigher educationAffect (linguistics)Willingness to paySustainable development

Abstract

fetched live from OpenAlex

This study aims to investigate similarities and differences in opinions related to sustainability and in the willingness to adopt sustainable behaviors between university members from Spain, Italy, and Mexico. An observational, cross-sectional, and comparative study was conducted in the years 2022 and 2023. A total of 1149 participants were included from 12 public universities and higher education institutes. The results indicate that the university community in the three countries demonstrates the ability to recognize and acknowledge the significance of environmental issues. However, few participants were trained or knew the initiatives promoted by their universities. Concerning the comparison of countries, Spanish participants tend to have more knowledge and positive beliefs about sustainability as compared to the others while, Italian and Spanish participants tend to be more concerned about the deleterious effects of non-sustainable behaviors and tend to have more positive attitudes as compared to Mexican participants.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.319
Teacher spread0.310 · 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 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 routes1
Has abstractyes

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