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Governing Household Waste Management: An Empirical Analysis and Critique

2016· article· en· W2507413325 on OpenAlexaffabout
Scott Cameron Lougheed, Myra J. Hird, R. Kerry Rowe

Bibliographic record

VenueEnvironmental Values · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsQueen's University
Fundersnot available
KeywordsGovernmentalityContext (archaeology)CitizenshipCorporate governanceSociologyHousehold wasteIdentity (music)Public administrationEnvironmental ethicsBusinessPolitical scienceEconomicsManagementLawEngineeringArchaeologyGeographyWaste managementPolitics

Abstract

fetched live from OpenAlex

We conducted a survey of residents of Kingston, Ontario, Canada, (n = 107) to understand their attitudes to and experiences of waste management and governance. Currently, the municipality is emphasising waste diversion and exploring new waste processing systems (WPS; e.g., incineration) to reduce costs. Using Foucault's governmentality theory, our data suggest Kingston's reliance on an attitude-behaviour-context model of behaviour change successfully fosters an environmental citizenship identity based on waste diversion (e.g., recycling). However, we argue that the neoliberal governmentality upon which the attitude-behaviour-context model is predicated elides the need for, and inhibits consideration of, broader societal change concerning urgent environmental issues involving 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.010
Science and technology studies0.0090.013
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations14
Published2016
Admission routes2
Has abstractyes

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