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Record W2341449040 · doi:10.5539/ass.v12n5p214

The Savings and Credit Cooperative of Royal Police Cadet Academy Limited: New Guidelines for Good Governance Reform in the Royal Thai Police

2016· article· en· W2341449040 on OpenAlexvenueno aff
Auschala Chalayonnavin

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsnot available
Fundersnot available
KeywordsCadetCorporate governanceLanguage changeDebtStandard of livingBusinessQuality (philosophy)AccountingFinanceLawPolitical science

Abstract

fetched live from OpenAlex

The fluctuations in the Thai economy since 1997 have had a big impact on the standard cost of living of the police officers. Many struggle to earn enough income to cover the expenses. Debt problems have put officers under a lot of stress affecting their standards of performance and encouraging corruption. The Savings and Credit Cooperative of Royal Police Cadet Academy Limited (RPCA Coop Ltd) has played a crucial role in improving a quality of life of the members by alleviating their financial problems. An evaluation of RPCA Coop Ltd operation revealed that it has achieved an objective to alleviate the members’ debt problems. RPCA Coop Ltd has helped the members to decrease their physiological needs and their standard cost of living and to become economically sufficient. When their physiological needs are met, they will desire to be well respected and to have job security through high performance efficiency in the police force.

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)0.019
metaresearch head score (Gemma)0.025
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0110.006
Open science0.0020.005
Research integrity0.0160.010
Insufficient payload (model declined to judge)0.0140.003

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 head0.049
GPT teacher head0.300
Teacher spread0.251 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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