Analysis of Togos economic and socio-political situation: challenges and perspectives
Bibliographic record
Abstract
After a long period of political instability that led to a sharp contraction of the economy and an unprecedented high level of poverty, Togo, in 2006, began the normalization of the situation. Over the past three years, considerable progress has been made by the Government. This has helped to restore a relatively calm political and social climate. These efforts were welcomed by the entire international community that cares more and more to help the country towards sustainable development. The Government should, however, step up efforts to address the major challenges like (1) consolidation of peace and social stability; (2) improving governance; (3) strengthening institutional capacity ;(4) consolidating the macroeconomic framework; (5) the rehabilitation of socio economic infrastructure; and (6) protection and improvement of living conditions of the people. As with other development partners in the country, the African Development Bank (ADB / ADF) is involved in the Togolese economic development. If these efforts are consolidated and supported with a peaceful socio-political climate, the foundations for economic growth and a sustainable economic development in Togo can be laid. Key words: Togo, poverty reduction, socio-political climate, Togo’s economic, strategy development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".