Local and International Factors Affecting Participation of Tanzanian Small and Medium Enterprises in Market Opportunity Brought by the African Growth and Opportunity Act (AGOA)
Bibliographic record
Abstract
The study aimed at assessing local and international factors that affect participation of Tanzanian Small and Medium enterprises in market opportunity brought by African Growth and Opportunity Act (AGOA). The study focussed on Tanzania local SMEs engaged in garments and textiles, handicrafts, leather goods, footwear and agro-processing subsectors. The study utilized mixed approach methods and involved a total of 129 respondents. Questionnaire and interview were the main tools for data collection. Information was collected from the owners and marketers of SMEs located in Dar es Salaam, the officials of Ministry of Industry and Trade as well as the Tanzania Ministry of foreign Affairs and East Africa Cooperation. Quantitative data was analysed using SPSS software and qualitative data was examined using MAXQDA software. Findings revealed that both local and international related factors were inhibiting Tanzanian SMEs from engaging in the AGOA market. Such factors have been narrated in this paper and recommendations have been given in order to increase engagement of Tanzanian SMEs in the AGOA market.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".