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Record W4293060564 · doi:10.1089/eco.2021.0067

Biospheric Values Predict Ecological Cooperation in a Commons Dilemma Scenario

2022· article· en· W4293060564 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEcopsychology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsLakehead UniversityNipissing University
Fundersnot available
KeywordsCommonsDilemmaSocial dilemmaValue (mathematics)Common-pool resourceSocial value orientationsPsychologySocial psychologyEcologyEconomicsMicroeconomicsBiology

Abstract

fetched live from OpenAlex

In ecological commons dilemma research, environmental values tend to be treated as a monolith. However, environmental values vary and they do not equally predict proenvironmental behavior. In this study, we investigated the impact of three kinds of proenvironmental values (egoistic, altruistic, and biospheric) on competitive and cooperative behavior in a hypothetical ecological commons dilemma scenario. Two hundred Canadian undergraduate students completed an online survey assessing proenvironmental value orientation and commons dilemma decision-making tendencies. In line with our hypothesis, controlling for demographic characteristics (e.g., gender) and key facets of social desirability (e.g., impression management), egoistic, altruistic, and biospheric values positively predicted competition, altruistic cooperation, and ecological cooperation, respectively, within the commons dilemma. Results show that to promote the sustainable consumption of shared ecological resources, it is prudent for educators, environmental managers, and policy makers to encourage the expression of biospheric values.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.939

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)0.0620.000

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 head0.260
Teacher spread0.250 · 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