Blending the Legal and Institutional Framework With the Economy of Communion as a New Paradigm for the Fight Against Corruption in Developing African Countries: The Case of Cameroon
Bibliographic record
Abstract
Corruption in Africa is a colonial legacy. However, this cankerworm grew in strength in the early 1990s as a result of the economic crisis that affected the Cameroonian and most of African economies in the late 1980s, stretching to the mid 1990s. As a result of this economic crisis, the currencies of most African States were devaluated and the salaries of workers were slashed. Extreme poverty then crept into the lives of these workers as they could barely meet up with their daily needs. To ameliorate these poor living standards, most workers resolved to corrupt practices and so corruption grew in strength and in might. African countries were propelled to the top of corruption rankings by corruption watchdog Transparency International. From thence, African governments have been relentless in their efforts to fight against corruption. This paper therefore carries out a critical analysis of the laws and institutions put in place for the fight against corruption in Africa with the case study being Cameroon. It equally assesses the extent of their success and the reasons for their failure. Above all it proposes a new paradigm for the fight against corruption in the developing countries of Africa which is the Economy of Communion.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".