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Record W3122306211 · doi:10.1016/j.envc.2021.100029

Single-use plastic bag policies in the Southern African development community

2021· article· en· W3122306211 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

VenueEnvironmental Challenges · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsDalhousie University
FundersAssociation of Commonwealth Universities
KeywordsBusinessPlastic bagEnforcementPlastic pollutionTourismPsychological interventionEnvironmental planningPublic policyEconomic growthPolitical sciencePollutionGeographyEconomicsEngineering

Abstract

fetched live from OpenAlex

The growing visibility of plastic pollution, particularly negative environmental impacts of single-use plastic bags, has entered the political debate, triggering policy interventions to control its manufacturing and use. This trend was also felt in Southern Africa, a region with high urbanization, leading to increased resource use and plastic consumption, heavily reliant on tourism, an industry highly impacted by plastic pollution. This paper reviews existing single-use plastic bag reduction policies in the Southern African Development Community (SADC). All 16 SADC members have announced a plastic bag reduction policy, but interventions vary in stages of implementation. Waste management emerged as the most important policy driver and over 55% of SADC members adopted a top-down approach in developing these policies to address these environmental challenges. Most SADC members with existing policies did not conduct public awareness campaigns, raising effectiveness issues. Further research on effective plastic bag reduction policy development, enforcement and monitoring would address an important knowledge gap.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score1.000

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)0.0010.001

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 head0.044
GPT teacher head0.204
Teacher spread0.160 · 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