Time, love and tenderness: Doctors’ online volunteering in Health Virtual Community searching for work-family balance
Bibliographic record
Abstract
BACKGROUND: This study will explore and understand the experience of doctors volunteering online in managing the boundaries between work and family in health virtual communities (HVC). METHODOLOGY: A qualitative case study approach was used to explore and understand how doctors volunteering online balances between work and family in a Health Virtual Community called DoktorBudak.com (DB). A total of seventeen (17) doctors were interviewed using either face-to-face, Skype, phone interview or through email. RESULTS: The results of this study suggested that doctors perceived the physical border at their workplace as less permeable though the ICT has freed them from the restriction to perform other non-related work (such as online volunteering (OV) works) during working hours. In addition, doctors OV use ICTs to perform work at home or during working hours, they perceive their work and family borders as flexible. Furthermore, the doctors used different strategies when it came to blending, whether to segment or integrate their work and family domains. CONCLUSION: This study has defined issues on work-family balance and OV. Most importantly this study had discussed the conceptual framework of work-family balance focusing on doctors volunteering online and how they have incorporated ICTs such as Internet technology to negotiate the work-family boundaries, which are permeable, flexible and blending.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".