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Record W4394726262 · doi:10.1142/s0219198924500087

Ecological Economics and Dynamic Games: A Systematic Literature Review

2024· article· en· W4394726262 on OpenAlex
Régis Chenavaz, Stanko Dimitrov, Shoude Li

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

VenueInternational Game Theory Review · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEconomicsMathematical economicsEcologyMicroeconomicsBiology

Abstract

fetched live from OpenAlex

Ecological and environmental economics are inherently dynamic systems requiring dynamic optimization tools. Understanding the interplay between environmental economics, ecological economics, and dynamic games is crucial. This paper presents a systematic literature review on ecological and environmental economics modeled with dynamic games. To be more specific, this systematic literature review analyzes a dataset of 88 peer-reviewed articles from international journals. This study identifies clusters related to resource management, taxation, and policy. It also reveals niche and motor research themes, such as policy, biological invasions, pollution, taxation, abatement, and efficiency, paving the way for future research avenues. By comprehensively examining the literature, this review provides insights into current and future challenges faced by companies, consumers, regulators, and society. It contributes to a deeper understanding of the complex relationship between ecological and environmental dynamics and the field of dynamic games in economics.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.001

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 head0.018
GPT teacher head0.256
Teacher spread0.238 · 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