WILL SMALL AND MEDIUM ENTERPRISES PROVIDE HIV/AIDS SERVICES TO EMPLOYEES? AN ANALYSIS OF MARKET DEMAND
Bibliographic record
Abstract
Abstract Background: Although many large businesses have begun offering HIV/AIDS prevention and treatment services to employees, the vast majority of small and medium sized enterprises (SMEs) have not. SMEs face constraints reducing their demand for services. This study identifies and evaluates those constraints to determine the extent to which SMEs can be expected to implement HIV/AIDS programmes, and to identify opportunities for strengthening the role of SMEs in South Africa's response to the epidemic. Methods: Structured interviews were conducted with a random sample of 80 SMEs located in KwaZulu Natal (KZN) and Gauteng provinces. Results: About one quarter of the companies sampled provided some HIV/AIDS services to employees and fewer than half incurred any direct costs to provide those services. Although 52 per cent of the companies believed they had lost employees to AIDS, few of those employees were regarded as critical to operations. AIDS accounted for 10 per cent of the overall annual employee turnover of 13 per cent. Few companies incur direct costs in recruiting or training, and just 30 per cent of permanent employees have access to employer sponsored healthcare. HIV/AIDS ranked 9th of 10 major business concerns faced by SMEs. Conclusions: Since managers believe few employees are leaving the workforce due to HIV/AIDS and SMEs appear to incur few costs to replace workers, managers are relatively unconcerned about HIV/AIDS. Serious demand‐side barriers exist in the market for HIV/AIDS services for SMEs. For most of the SMEs in our survey, the constraints are too great to expect SMEs to play a major role in the national response to AIDS without assistance.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".