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Record W4200438533 · doi:10.3390/en14238189

The Impact of Government Subsidies on Single-Channel Recycling Based on Recycling Propaganda

2021· article· en· W4200438533 on OpenAlexaff
Fangfang Zhang, Hao Wang, Xiaoyu Wu

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Toronto
FundersMinistry of Education of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsSubsidyGovernment (linguistics)RevenueUnit (ring theory)BusinessChannel (broadcasting)Government revenueEnvironmental economicsEconomicsPublic economicsEngineeringFinanceMarket economyTelecommunications

Abstract

fetched live from OpenAlex

The recycling of waste products is an important way to achieve global sustainable development. To analyze the impact of different objects of government subsidies on single-channel recycling based on recycling propaganda, four theory game models of single-channel recycling based on government subsidies and recycling propaganda are established. By comparing and analyzing the effects of different subsidies and propaganda strategies on the recycling of waste products in the four models, this article mainly draws the following conclusions: the government selecting different objects to subsidize has the same effect on the unit recycling price, quantity, and revenue of waste products; when the government subsidizes the processors, the consigned recycling price of waste products will increase, but when the government subsidizes recyclers, it will decrease; when the propagandist is determined, the optimal value of propaganda is related to the sensitivity of residents to the unit recycling price of waste products, the unit propaganda of waste products, and the expenses of propagating waste products.

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.

How this classification was reachedexpand

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2021
Admission routes1
Has abstractyes

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