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Record W4312635355 · doi:10.5334/wwwj.85

Waste in Zero-Waste Households: The Power of Materials and Norms in Everyday Consumption

2022· article· en· W4312635355 on OpenAlexaff
Mallory Xinyu Zhan

Bibliographic record

VenueWorldwide Waste · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsEveryday lifeReflexivityConsumption (sociology)EthnographySociologyPower (physics)Zero wasteProvisioningMarketingBusinessAestheticsComputer scienceEngineeringSocial sciencePolitical scienceWaste managementArt

Abstract

fetched live from OpenAlex

This research examines the challenges of everyday waste minimization of ‘zero waste’ practitioners in Chinese cities. Drawing on 45 in-depth interviews and virtual ethnography of a zero-waste community, this article details the processes during which different types of waste were ‘inevitably’ produced in everyday practices, such as those related to shopping and gifting, food provisioning and eating, binning and composting. Using theories of social practice, this article turns away from focusing on individual awareness, behavior, and choice, and instead seeks to explain how practices that people come to perform can be reproduced and reinforced despite individuals’ commitments to change. The findings illuminate how waste generation is subject to culturally and collectively constructed norms and rules, key social relations of love and care, and is embedded in the material arrangements that make up everyday life. The research sheds light on the importance of paying attention to both the more routinized and reflexive aspects of everyday life, and the power of diverse actors in affecting and shaping daily activities of consumption and waste.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.217
Teacher spread0.202 · 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 designBench or experimental
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

Citations5
Published2022
Admission routes1
Has abstractyes

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