Anatomy of the Privatization of State-Owned Enterprises (SOEs) in Ghana: Implication for Policy and Accountability
Bibliographic record
Abstract
With the administrative and operational functions of State-Owned Enterprises (SOEs) becoming increasingly complex and sophisticated among developing countries by the 1980s, privatization was recommended by the IMF/World Bank as a remedy to these institutional deficiencies . This is contingent on the neoclassical debate that private ownership rather than public ownership of management and operations of SOEs results in prudent policy process and accountability. Therefore, this study sought to assess the validity of this assertion by employing the Principal-Agent theory in assessing the level of accountability between the citizens (principal) and the government (agent) during private ownership of service delivery. As a qualitative study, this paper adopts unobtrusive content analysis of an empirical study of the privatization of Ghana Water Company Limited (GWCL). The government (agent) under the Principal-Agent theory is to ensure that the private operator, Aqua Vitens Rand Limited (AVRL) respects the terms of divestiture, while upholding the principles of accountability. However, the findings of the study suggest that the failure of government (agent) to uphold core accountability mechanisms such as transparency, accessibility to information, sense of ownership, responsiveness, and conformity to established monitoring and evaluation measures, contributed to the inability to achieve key performance targets, leading to the unsuccessful policy outcome of the privatization contract. This paper, therefore, argues that the failure to adopt accountability mechanisms in the divestiture of SOEs will inevitably compromise administrative policy outcomes.
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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 | 0.001 | 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 | 0.003 | 0.012 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".