COVID-19 Crisis Management of the Readymade Garment Sector in Bangladesh
Bibliographic record
Abstract
The first cases of the virus that has been codenamed coronavirus disease 2019, or COVID-19 in short, were recorded in the city of Wuhan from the Hubei province in China in December, 2019. By March 26, 2020, international retailers cancelled orders worth US$2.67 billion of garment exports of Bangladesh. Like other states imposing lockdown, the Government of Bangladesh (GoB) followed suit by the final week of the month of March and announced a public holiday starting from March 26, 2020. As events transpired the country eventually went into a complete lockdown to curb the spread of the virus. The research paper follows a temporal narrative dividing it in three main sections: National Holidays and Initiating the Industrial Lockdown; Industrial Lockdown Period; and Post- Industrial Lockdown. Against the backdrop of the pandemic and global downturn in economic activity, this research looks into the effects of the contagion on the RMG sector of Bangladesh up and until the end of May, 2020, and assesses how well the GoB has been able to manage the crisis, and in the process provides insights into the demands, health and livelihood of 4.1 million workers that the sector employs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".