Bibliographic record
Abstract
Introduction: WFH (work from home) is the today’s new normal. It has changed industry dynamics and given the ease and flexibility of being at office remotely, though it compromises on the traditional boundary between work-life balance. Since the beginning of the pandemic in 2020, the pluses and minuses have been debated extensively and now with gradual attempts of return to normalcy, an important question arises for companies and their employees whether WFH is the ‘semi-vacation’ like boon it seemed to be or it is like that dreaded Monday which doesn’t seem to end ever after work hours. Aims: To study the perceived stress and anxiety in I.T. professionals who are working from home Methodology: The study was initiated after taking approval from institutional ethics committee, Osmania Medical college. Written informed consent was obtained from participants and data was collected using google forms from various I.T. professionals who are working from home. Perceived Stress Questionnaire (PSQ) and Hamilton Anxiety Rating Scale(HAM-A) were included in the google form. Data analysis was done using SPSS software. Results: A quarter of the participants had PSQ Index greater than 0.5 suggesting higher perceived stress levels. As per HAM-A, about 60% participants had Mild Anxiety, less than 20% had moderate anxiety, 10% scoring in the range of moderate to severe anxiety and about 5% had severe anxiety.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.839 | 0.757 |
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".