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Record W3188616141 · doi:10.46754/jssm.2021.07.015

THE IMPLEMENTABILITY OF LOW CARBON CITIES IN THAILAND: A CASE OF HAT YAI CITY MUNICIPALITY

2021· article· en· W3188616141 on OpenAlexaboutno aff
Thitichaya Boonsom, Chanisada Choosuk

Bibliographic record

VenueJournal of Sustainability Science and Management · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsCivil societyEuropean unionFocus groupKyoto ProtocolPolitical scienceEconomic growthGeographyBusinessEnvironmental protectionGreenhouse gasPoliticsEconomicsEconomic policy

Abstract

fetched live from OpenAlex

The movement for low carbon cities has substantially received attention and cooperation from many countries around the world, including developed and developing countries, which have and have not ratified the Kyoto Protocol. Many developed countries and members of the Annex-I parties to the Kyoto Protocol (e.g., China, Japan, United Kingdom, Canada, America, Germany, and other European Union members) have already implemented schemes of low carbon cities using multi-actor mechanisms that form robust participation among public sectors, private entities, civil societies, and local communities (Van der Heijden, 2016). Currently, low carbon cities are widespread. Many of these cities are in 27 European Union nations (daGraaCarvalho et al., 2011)to ensure that 20% of final energy Abstract: This study aimed to describe the importance of low carbon policies and address strategies to promote community participation in implementing low carbon cities. Hat Yai City Municipality was observed as a case study on policy and participation. Although Hat Yai is an important economic city in Southern Thailand, it is prone to climate change threats and impacts. The study employed a qualitative design. Primary and secondary data were collected from documents, semi-structured interviews, focus group discussions, and participant observations. Thirty-seven key informants comprising 7 policy representatives of Hat Yai City Municipality, 20 stakeholders in low-carbon model communities, 4 private sector members, 2 media workers, 2 NGO members, and 2 civil society representatives were involved. Through content analysis and data triangulation, the results revealed key influencing factors of low carbon city implementation. The results revealed that the success of low carbon cities depends on the three P-S-P factors. The initial letter P refers to policies at the national and local levels. The following letterS refers to stakeholders who should be fostered on networking and cooperation. The final letter P refers to participation, which should be encouraged through context-based promotion of learning, whereas a cooperation network should be expanded to reach all stakeholders in society.

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)0.007
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.050
GPT teacher head0.298
Teacher spread0.248 · 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 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
Published2021
Admission routes1
Has abstractyes

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