Case Study in a Malaysian Public Agency on an Asset Management-Moving Towards the Accrual Basis of Accounting
Bibliographic record
Abstract
As part of the strategic reform of Malaysian public services under the Government Transformation Program (GTP), accrual accounting is expected to be fully adopted in public sector financial reporting commencing on 1 January 2015, in order to ensure alignment with the global accounting standards. Consequently, in order to access the government effectiveness of moving towards the accrual basis of accounting, this study is to examine the asset management system in a Malaysian public agency; to evaluate the extent of compliance with MPSAS 17, Property, Plant and Equipment (PPE), IPSAS 26, Impairment of Cash-Generating Assets and IPSAS 21, Impairment of Non-Cash Generating Assets. Using qualitative approach, a preliminary study was conducted via interviews and through obtaining documents. The findings include the following: MPSAS17 has not been strictly adhered to and software is used to monitor the assets; however, the disposal of assets is a manual process and is not automated. The study also discussed any weaknesses pertaining to the said asset accounting system, and suggested recommendations for improvement thereon.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".