CARING FOR “PARENTLESS” CHILDREN: AN EXPLORATION OF WORK STRESSORS AND RESOURCES AS EXPERIENCED BY CAREGIVERS IN CHILDREN’S HOMES IN GHANA
Bibliographic record
Abstract
The experience of stress by workers in any work environment has negative impacts on employee health and productivity. However, work resources are known to have possible neutralizing impacts on the negative effects of stress depending on the availability of those resources and the extent to which employees are able to identify and utilize them. This study explores this stress–resource relationship and its implications in a work context where the lives of vulnerable children depend on the wellbeing and productivity of their employed caregivers. Qualitative exploratory techniques were used to investigate the sources and nature of stressors experienced by caregivers and the extent to which caregivers identify and utilize resources available in that work environment. Participants comprised 41 caregivers from 2 children’s homes in Ghana. It emerged that aspects of the work environment that were identified as stressors also tended to be identified as resources for caregivers. These included the children, the work environment, institution–community relations, and relationships between caregivers and their own families. Caregiver faith and intrinsic motivation stood out as the most frequently reported of the resources upon which caregivers drew to cope with their jobs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".