Factors Influencing the Acceptance of International Public Sector Accounting Standards in Cameroon
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is a growing consensus that governments should be held financially accountable, and Cameroon like many developing countries faces the challenge of running a sound government accounting system that guarantees accountability and transparency. Governments strive to adopt a new public management philosophy which focuses on the change in management practices of the public sector towards more private sector practices with the aim of rendering the public sector more cost effective and efficient. The transition from cash to accrual based International Public Sector Accounting Standards (IPSAS) in order to overcome the rising unaccountability and opaqueness in the use of public sector finances becomes a daunting task. In this respect, Cameroon tends to accept international accounting standards that can be adapted easily to its local situation and also make its financial reports more reliable, standardised, comparable, and attractive on the international scene. With this backdrop, the paper sought to investigate the factors influencing the acceptance of government accounting reforms in general and IPSAS in particular in Cameroon. A survey was conducted in the Ministry of Finance (MINFI) and the Ordinary Least Squares (OLS) and Ordered Logistics Estimation techniques used. The main findings revealed the determining factors of IPSAS acceptance in Cameroon namely: knowledge and awareness, institutional organisation, staff training and recruitment, management information system, qualification, sex, implementation cost, political support, and age. The paper ends up proposing a careful study of these factors by the government for any successful public sector accounting reform and IPSAS acceptance to take place.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it