A study on welfare policies of Amara Raja Power System Limited: A case study in Tirupati
Bibliographic record
Abstract
I conducted a Survey Method through Structured Questionnaires in the Employees of ARPSL Tirupati. The convenience sampling procedure is used for the data collection, sampling size is116 through Personal Interview and Percentage analysis and Chi-square tests are used. Finally, in this paper, I found the result that the Majority of the respondents said that Medical and First aid facilities provided by the Company are Excellent. Canteen facilities are good because the cleanliness maintained, proper storage of raw materials, food served is nutritious quality and quantity of food served is good. Working conditions of the company in respect to Ventilation, Lighting, Temperature, Seating arrangements, cleanliness inside working premises are very good. Employee satisfaction levels on Social security benefits like PF, ESI, Gratuity, SAS and Benevolent Fund schemes provided by the company is good. Transport facilities, Bachelor Hostel facilities, Family quarter’s facilities, Recreation facilities provided by the company are good.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".