Not business as usual: Engaging the corporate sector in India’s TB elimination efforts
Bibliographic record
Abstract
India has the highest global burden of tuberculosis (TB), accounting for a quarter of the worldwide TB disease incidence. Given the magnitude of India's epidemic, TB has enormous economic implications. Indeed, the majority of individuals with TB disease are in their prime years of economic productivity. Absenteeism and employee turnover due to TB have economic ramifications for employers. Furthermore, TB can easily spread in the workplace and compound the economic impact. Employers who fund workplace, community, or national TB initiatives stand to gain directly and also enjoy reputational benefits, which are important in the era of socially conscious investing. Corporate social responsibility laws in India and tax incentives can be leveraged to bring the logistical networks, reach, and innovative spirit of the private sector to bear on India's formidable TB epidemic. In this perspective piece, we explore the economic impacts of TB; opportunities for and benefits from businesses contributing to TB elimination efforts; and strategies to enlist India's corporate sector in the fight against TB.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".