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Record W3135695754 · doi:10.1002/pam.22325

Skipping the Bag: The Intended and Unintended Consequences of Disposable Bag Regulation

2021· article· en· W3135695754 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

VenueJournal of Policy Analysis and Management · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsImpact
Fundersnot available
KeywordsExternalityUnintended consequencesPlastic bagBusinessPublic economicsProduct (mathematics)Consumption (sociology)Environmental regulationNatural resource economicsCommerceEconomicsMicroeconomicsWaste managementLawEngineering

Abstract

fetched live from OpenAlex

Abstract Regulation of goods associated with negative environmental externalities may decrease consumption of the targeted product, but may be ineffective at reducing the externality itself if close substitutes are left unregulated. We find evidence that plastic bag bans, the most common disposable bag regulation in the U.S., led retailers to circumvent the regulation by providing free thicker plastic bags, which are not covered by the ban. In contrast, a regulation change that replaced the ban with a small tax on all disposable bags generated large decreases in disposable bag use and overall environmental costs. Our results suggest that narrowly defined regulations (such as plastic bag bans) may be less effective than policies that target a more comprehensive set of products, even in the case when the policy instrument itself (a tax rather than a ban) is not as strict.

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 categoriesnone
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 score0.652
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.226
Teacher spread0.207 · 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