Accounting, auditing and accountability research in Africa
Bibliographic record
Abstract
Purpose The purpose of this paper is to discuss developments in governance in Africa and the opportunities this offers to accounting, auditing and accountability researchers. The paper also provides an overview of the other contributions in this accounting, auditing and accountability special issue. Design/methodology/approach This paper provides a contemporary literature review on governance and accountability in Africa, identifying the key developments in public sector reform and the research gaps that still need to be filled. While the paper focuses on Sub-Saharan Africa, the authors draw on examples from Ghana, Kenya, and South Africa – geographically representing east, west, and south of the continent. Findings The paper finds that governance has emerged as a crucial issue that has a significant effect on the economic development of African countries. This has been associated with a myriad of reforms which range from anti-corruption measures to public financial management reforms. The authors find that the implementation and effects of these reforms have not been adequately researched by accounting scholars. Research limitations/implications This is a review of a limited literature. Empirical research and a more comprehensive review of the literature from public administration and other disciplines might provide other new insights for research on governance in Africa. A further limitation is that the study has focused on a review of the most recent reforms while earlier reforms should be of particular interest to accounting historians. Originality/value This paper and other contributions to this special issue of AAAJ provide a basis and an agenda for accounting scholars seeking to undertake interdisciplinary research on Africa.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.019 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".