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Record W1992721300 · doi:10.1109/smc.2013.304

Online Gaming for Sustainable Common Pool Resource Management and Tragedy of the Commons Prevention

2013· article· en· W1992721300 on OpenAlexfundno aff
Tyler Pierce, Kaveh Madani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
FundersUniversität ZürichMcGill University
KeywordsTragedy of the commonsCommon-pool resourceCommonsSustainabilityTeamworkNatural resourceKnowledge managementExternalityResource management (computing)Resource (disambiguation)Corporate governanceSocial dilemmaBusinessComputer scienceEconomicsPolitical scienceManagementEcologyMicroeconomics

Abstract

fetched live from OpenAlex

Tragedy of the commons is a well-known concept concerning the use, or rather abuse, of common pool resources. Educating those involved by teaching the long-term consequences of overuse and the benefits of sustainability is important to preserving natural resources. To study the effects that different institutions and characteristics had on participants, a web-based water sharing game called Irrigania was used as a tool to analyze different scenarios and facilitate better understanding of the externalities associated with governance and management of common pool resources in a class of graduate civil and environmental engineering students at the University of Central Florida. Game-based learning has been found to increase soft skills, such as critical thinking, creative problem-solving, and teamwork through multiple orientations of learning theory. Preliminary use of Irrigania has identified communication, cooperation, information disclosure and social learning as factors promoting a shift towards sustainable resource use.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.220

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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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 designSimulation or modeling
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

Citations8
Published2013
Admission routes1
Has abstractyes

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