Working conditions, health and exhaustion among social workers in Germany
Bibliographic record
Abstract
The aim of the study is to analyse the working conditions of social workers and their health. The data basis for secondary analysis is the representative 2018 BIBB/BAuA survey of employed persons in Germany. Three hundred forty-one of the interviewed 20,012 employed persons were social workers. They were on average 42.7 years old. Seventy-one per cent of social workers were women. Ten per cent of social workers have officially recognised disabilities. The cognitive and emotional demands were greater for social workers than for other professions. Social workers reported more often than other professions that their job frequently puts them in emotionally stressful situations (23% vs. 12%). The emotional demands were associated with general state of health. Forty-one per cent of social workers often felt emotionally exhausted in the past 12 months (vs. 26% in other professions). This proportion strongly increased with the number of conditions on work intensity. A quarter of the social workers complained about both frequent physical and emotional exhaustion during the past 12 months. Their sickness rate was disproportionately high. These results show occupational health risks and potentials for behavioural and situational prevention in social work. More health promotion, company integration management and risk assessments at work are recommended.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".