What Is Our Added Value? A Systematic Analysis of Epidemic Narratives in the Social Work Literature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article addresses social work’s singular conceptual and analytical contribution to the field of epidemics. A systematic literature review was conducted to analyze how social work studies overlap to construct epidemic narratives. The author collected 601 articles from the Social Services Abstracts database and carried out a targeted search within 20 social work journals. Five epidemic narratives were identified: (1) a psychosocial consequences narrative, (2) a social work competence narrative, (3) a social risk factors narrative, (4) a misinformation narrative, and (5) a power matrix narrative. Results highlighted the social success of psychosocial perspectives prevalent in classic public health narratives. This understanding relies on a “politics of access” perspective and advocates for the improvement of current social services. The findings revealed that social work does not have a conceptual specificity in the field of epidemics but, rather, its current distinctive contribution mostly lies in its use of social work–centric inquiries that analyze social work practices and describe the consequences experienced by social work actors during epidemics. The author argued that the social work literature could benefit from analyses informed by a “politic of emancipation” that are less prominent in the analyzed studies. Avenues for future research are considered.
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.
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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.024 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 it