Factors Influencing Participation of Informal Sector Workers in Formal Social Security Schemes in Dodoma City, Tanzania
Bibliographic record
Abstract
Social security is widely recognized as a basic human right. However, in most developing countries, majority of the population, especially in the informal sector is not covered by existing social security schemes. This paper examines factors influencing informal sector workers’ participation in the formal social security schemes in Dodoma City, Tanzania. The specific objectives of the paper are to 1) identify the type of economic activities performed by informal sector workers, and 2) analyze the determinants of informal sector workers participation in formal social security schemes. The paper draws on survey data collected from 184 informal sector workers’ through structured interviews and documentary review, and analyzed for descriptive statistics, chi-square test and binary logistic regression. The findings revealed that a relatively higher proportion female (56%) than male (44%) were involved in the informal economic activities, mainly food vending (32%), selling cereals (20%) and petty shops (18%). Only about one quarter of the informal sector workers (23%) were members of the formal social security schemes, and a substantial proportion was involved in the relatively informal schemes, such as village community banks (67%), savings and credit cooperative societies (59%) and rotating saving and credit associations (6%) as alternatives to formal social security schemes. The factors that significantly influenced informal sector workers’ participation in the formal social security schemes were sex, contribution rates, monthly income, capital and nature of the business. Given the low participation of informal sector workers in the formal social security schemes, it is recommended that deliberate efforts should be put in place to educate informal sector workers on the importance of the social security schemes, including the benefits offered by the schemes. Similarly, social security schemes should set their monthly contribution rates at a level that is affordable to informal sector workers given their relatively low incomes, and design benefits packages that fit the need of the informal sector workers.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".