Assessing Botswana’s textiles export trade potential using the gravity model
Bibliographic record
Abstract
Through the application of the gravity trade model technique, the study investigates countries for which Botswana has unrealized export trade potential in textile products. The estimated results indicate that Canada, Denmark, Finland, Ghana, Mozambique and Switzerland are the export destinations to which Botswana should increase its export of textile products as these countries have untapped market potential for such products. The research also found that existence of unrealized destinations to which Botswana should increase its export textile products as these countries have untapped market potential for such products. The research also found that existence of unrealized export potential in this sector was as a result of a number of issues including import barriers put by the importing country’s major trading partners as well as other problems from Botswana’s side. These barriers and hindrances to Botswana’s sectoral exports include stringent rules of barriers put by the importing country’s major trading partners as well as other problems from Botswana’s side. These barriers and hindrances to Botswana’s sectoral exports include stringent rules of origin (RoO),low product quality inadequate international marketing and unrecorded informal trade.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".