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Record W2415868115 · doi:10.1177/1086026616652667

How Do Money and Time Restrictions Influence Self-Constraining Behavior in Polluting the Commons?

2016· article· en· W2415868115 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.

Bibliographic record

VenueOrganization & Environment · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsCommonsTragedy of the commonsSocial dilemmaDilemmaCommon-pool resourceConstraint (computer-aided design)BusinessGovernment (linguistics)Consumption (sociology)Environmental economicsPublic economicsEconomicsNatural resource economicsMicroeconomicsEngineeringPolitical scienceLawSociologySocial science

Abstract

fetched live from OpenAlex

Commons are resources shared by a group of people, and are studied using the commons dilemma paradigm. Despite Hardin’s prediction that the only sustainable management options are government regulation or private ownership, sustainable commons management has been observed with unregulated groups; however, global commons such as the atmosphere and oceans seem to conform to the prediction of “tragedy” because self-interests among users lead to degradation of the commons through overuse. The present study examined whether the factors of commons type (consumption or waste disposal) and cost (money or time) influence individual self-constraint in harvesting/polluting decisions to prolong the longevity of the shared resource, in the absence of social communication. Results indicate an interaction of the two factors: Individual self-constraint was greatest with the combination of disposal commons and time cost. These findings suggest that creative strategies to manage global commons may be possible, at least for waste-disposal commons.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.447

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)0.0000.000

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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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