Analyzing the African Continental Free Trade Area (the AfCFTA) from an Informality Perspective: A Beautiful House in the Wrong Neighborhood
Bibliographic record
Abstract
Abstract The article critically explores the African Continental Free Trade Area (AfCFTA) from an informality perspective. The informality perspective sees unofficial rules, norms, practices, processes, actors, and decision-making structures as driving forces of the social world. They are ontologically prior to and building blocks of their formal counterparts. From this viewpoint, the failure to design the AfCFTA from the informal economy baseline makes it an unfit trade agreement for the African continent. Those who drafted the agreement, its supplementary protocols and annexes, and the decision-makers who signed as well as ratified them neglected the informal trading actors and unregistered enterprises in Africa. Rather than building the agreement around unregistered small-to-medium-scale enterprises, operated mostly by women and the youth, the AfCFTA and its legal instruments envisioned a utopian African trade market without them. The drafters and decision-makers of the AfCFTA seem to operate on the basic principle of no formalization and no gain from the free trade agreement. The result is a serious mismatch. The formally oriented AfCFTA is supposed to govern the largely informal African trading ecosystems. The failure to mainstream the informal economy in the AfCFTA makes the African free trade agreement look like, to use a house metaphor, a beautifully constructed house located in the wrong neighborhood. The article substantiates this claim and shows its implications for the Pan-African integration project and the study of international relations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".