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Consumers, cars and communities: the challenge of sustainability

2001· article· en· W1849309036 on OpenAlexaff
John W. Auld

Bibliographic record

VenueInternational Journal of Consumer Studies · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHuman settlementSustainabilitySubsidyFundamental human needsBusinessMarket failurePublic policyEconomicsEconomic growthMarket economyEngineering

Abstract

fetched live from OpenAlex

Abstract The huge subsidization of sprawling development and the unbridled use of the private automobile needs to be brought to the forefront of public policy debate, not left to the excesses of the market‐place. To do this we need citizens‐in‐the‐community, not consumers‐in‐the‐market. The present costly and unsustainable situation of our human settlements is a result of a profound failure in public policy; a failure that resulted when we left the fate of our human settlements to the vagaries of the market‐place. We can no longer rely on the present subsidized, distorted, market‐place system approach to designing, building and operating our human settlements. The consequences have been disastrous for human welfare, health and safety, and the natural environment upon which all life depends.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.030
Scholarly communication0.0120.009
Open science0.0010.008
Research integrity0.0090.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.056
GPT teacher head0.385
Teacher spread0.329 · 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 designNot applicable
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

Citations9
Published2001
Admission routes1
Has abstractyes

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