Determinants and constraints of women’s sole-owned tourism micro, small and medium enterprises (MSMEs) in Tanzania
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper explores the determinants and challenges affecting women sole owners of tourism-related enterprises. It identifies factors that determine sole ownership, assesses the extent to which women participate as sole owners and the challenges encountered in establishing and operating enterprises. Primary data on 475 women-owned enterprises is analysed using a probit model. We find that post-primary education, attendance of specialised training in tourism, engagement in other economic activities, and being previously employed reduces the likelihood of solely owning a business, while initiation of the business idea increases it. We recommend offering women entrepreneurial education to enable them acquire experience, develop right attitudes and foster networks for entrepreneurship. Furthermore, increasing awareness on availability and access to the Women Development Fund (WDF) and strengthening the enforcement of laws governing ownership of land could provide women with start-up capital and means to access formal loans that require collateral.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it