Bibliographic record
Abstract
Life is a mixture which contains all the strands together. A person should have both love and work in life to make it more happy and healthy. Work is an important part of everyone’s day to day life. In a day, on an average everyone spent at least eight to ten hours for work which is a part of our entire life. Human values were given inadequate attention by traditional management. Earlier it was like the employees were used for physical and material needs. The aspect of QWL was first introduced by Davis in 1970s. In 1972 the first International Conference on QWL was held at Toronto. The concept was introduced for reducing employee turnover and employee well being on the services offered by them. Quality of work life refers to the level of satisfaction or dissatisfaction of a job environment for the employees working in an organization. The study attempted to enumerate the satisfaction level of the employees in their current job environment at Apollo. With this information Apollo can strengthen the factors which provide better QWL. In short, the study helped the company to make the work place a pleasant and highly motivating one for employees. KEYWORDS: QWL, Employee attitude, Employee satisfaction, Motivation, Organisation
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 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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".