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Record W2191972211 · doi:10.24102/ijes.v4i2.482

Measuring Toyota Citizens' Eco-awareness: Is the City’s Eco-policy More Recognized?

2015· article· en· W2191972211 on OpenAlexvenueno aff
Hiroshi Ito

Bibliographic record

VenueInternational Journal of Environment and Sustainability · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessArchitectural engineeringEngineering

Abstract

fetched live from OpenAlex

In 2009, Toyota City was selected as an environmental model city by the Japanese government. The city has been working on addressing environmental issues and raising citizens’ awareness of its eco-policy focusing on five relevant themes: transportation, forests, the urban center, industry, and public welfare and livelihood. In 2012, surveys were conducted in Toyota City to examine how much citizens recognized the eco-policy. The study showed that less than 40% of Toyota City citizens were aware of the fact that the city was designated as an environmental model city. Using the same research method as the 2012 study, a similar survey was conducted in 2014 to examine how the citizen’s awareness of the eco-policy had shifted. The findings show little sign of improvement in citizens’ eco-awareness: the recognition rate of most topics had dropped in the 2014 findings compared to those of 2012. This paper explores possible reasons for the results and makes suggestions for improving eco-awareness.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.294
Teacher spread0.266 · 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.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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