Bibliographic record
Abstract
This paper attempt to analyze the Covid -19 pandemic impact on the gross value added of the Indian service sector. The purpose of present study is to examine the relationship between the number of Covid -19 confirmed cases in India and gross value added of service sector and sub-service sector of India. The results of the study suggest that number of Covid -19 confirmed cases have a negative impact on the gross value added of the service sector and sub-service sectors of India. However, the negative impact of Covid -19 confirmed cases on the gross value added of the service sector and sub-service sectors of India is not statistically significant. This study also suggests what steps the government can take to revitalize the service sector. The present study is quantitative. For the purpose of study data collected from FY 2019 to the first quarter of FY 2021-22. The study is based on secondary data. The database of the Ministry of Statistics and Programme Implementation was the source of information for the Indian Service Sector GVA and the Ministry of Health and Family Welfare (MoHFW) was the source of information for the number of confirmed Covid -19 cases in India.
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.
How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".