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Record W1800245865 · doi:10.1002/pam.21675

Spillover Effects of Voluntary Environmental Programs on Greenhouse Gas Emissions: Lessons from Mexico

2012· article· en· W1800245865 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Policy Analysis and Management · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsYork University
FundersCommission for Environmental Cooperation
KeywordsSpillover effectGreenhouse gasClubTurnoverBusinessNatural resource economicsEnvironmental economicsEnvironmental protectionEnvironmental scienceEconomicsEcologyMicroeconomics

Abstract

fetched live from OpenAlex

Abstract We compare the environmental performance of voluntary environmental programs (VEPs) with different attributes. Using club theory, we argue that the differential performance of VEPs is due in part to their specific design attributes that will either enhance or diminish their ability to improve both targeted and untargeted environmental impacts. We analyze two VEPs in Mexico, the global standard ISO 14001 and the local standard Clean Industry. These two VEPs differ in the stringency of the standards and in their ability to sanction noncompliant facilities. These differences ensure that firms adopting the local standard are less likely to shirk their responsibilities and enhance potential spillover effects on untargeted environmental emissions. Our empirical results support our hypotheses and show that the local Clean Industry program is more effective in improving both targeted (toxic emissions) and untargeted environmental impacts (greenhouse gas emissions).

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 score0.087
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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