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Record W3095860406 · doi:10.1089/eco.2019.0078

Entitlement Predicts Lower Proenvironmental Attitudes and Behavior in Young Adults

2020· article· en· W3095860406 on OpenAlexaff
Steven Arnocky, Jessica Desrochers, Ashley Locke

Bibliographic record

VenueEcopsychology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsNipissing University
Fundersnot available
KeywordsEntitlement (fair division)PsychologySocial psychologyTraitAction (physics)Construct (python library)MediationEnvironmentalismPolitical scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Environmental advocates commonly describe ecological problems as being caused, at least in part, by the psychological construct of human entitlement. Nevertheless, the concept of trait entitlement, as an individual difference variable, has not yet been considered in relation to proenvironmental attitudes and behavior. This research examined whether entitlement among young adults correlates with environmental attitudes and actions. Results showed that individuals who were high in entitlement scored lower in attitudes in favor of protecting the environment, self-reported environmental behavior, and were less likely to engage in observable environmental action by way of donating money earned from the study to an environmental cause. Conversely, those high in entitlement were more in favor of human utilization of the environment and supported geoengineering efforts. Mediation analysis showed that environmental attitude mediated the links between entitlement and both donating and conservation behavior. Together, these results highlight the role of trait entitlement as a barrier to environmentalism.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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 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

Citations6
Published2020
Admission routes1
Has abstractyes

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