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Record W4413244971 · doi:10.53832/evidence-fund.0039

Empowering Thailand's Digital Government with Open Data

2024· report· en· W4413244971 on OpenAlexaboutno aff
Open Data Institute Open Data Institute

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsnot available
FundersForeign, Commonwealth and Development OfficeGovernment of the United Kingdom
KeywordsOpen governmentGovernment (linguistics)Agency (philosophy)Context (archaeology)Work (physics)Digital ecosystemDigital governmentOpen dataDigital literacyBusinessPolitical sciencePublic relationsEconomic growthPublic administrationDigital transformationKnowledge managementGeographySociologyEngineeringSocial scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

This study examines the adoption and use of open data to empower digital government in Thailand. It assesses the current data ecosystem, including policies, infrastructure, and data literacy within Thai government agencies and wider society. The research draws on comparative case studies from countries including the UK, France, Canada, and Uruguay to inform its analysis of the Thai context. This work scopes opportunities and provides advice for Thailand’s Digital Government Development Agency.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.109
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0050.002
Open science0.0040.004
Research integrity0.0000.000
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 head0.098
GPT teacher head0.396
Teacher spread0.298 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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