MétaCan
Menu
Back to cohort
Record W4210487126 · doi:10.1111/meca.12381

Reclamation of a resource extraction site: A differential game approach

2022· article· en· W4210487126 on OpenAlex
Simone Marsiglio, Nahid Masoudi

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

VenueMetroeconomica · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsMemorial University of Newfoundland
FundersUniversità di Pisa
KeywordsLand reclamationLeaseOrder (exchange)Differential (mechanical device)BusinessHomogeneousNatural resource economicsEnvironmental economicsEconomicsMicroeconomicsFinanceEngineeringEcology

Abstract

fetched live from OpenAlex

Abstract We study an extraction site reclamation problem in a two‐player differential game setting over a finite time horizon. Environmental regulation requires each firm to engage in reclamation efforts during the entire lifespan of the extraction site and to pay an abandonment reclamation fee at the end of its lease term for the unclaimed pollution caused by firms’ activities. Firms determine their reclamation efforts in order to minimize their reclamation cost. We analyze and compare individual firms’ choices and the pollution stock in the noncooperative and the cooperative cases by distinguishing between situations in which firms are homogeneous and heterogeneous. We study the case in which firms have different lease durations and different degrees of environmental liability. We show that the dynamics of the reclamation efforts may be substantially different under noncooperation and cooperation, and in both cases, it is mainly determined by how the rate of time preference and the growth rate of firms’ liabilities compare. Moreover, in all scenarios, the reclamation efforts generally rise with the degree of liability and fall with the lease duration, suggesting that in order to promote better environmental outcomes, the regulators should carefully determine the lease conditions by introducing intra‐term reclamation fees along with stringent environmental accountability.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.065
GPT teacher head0.240
Teacher spread0.175 · 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