Social Work Perspectives: Conceptualising Youth Mental Health Through Trauma-Informed Systems Thinking
Bibliographic record
Abstract
The following literature review explores theoretical understandings of social workers and the distinctiveness of social work conceptualisations of young people within mental health fields. Clarifying the distinctiveness of social work perspectives is critical for encouraging a collective professional identity underpinned by a consistent philosophy where the social work role is guided by evidence-based theories. The overall findings support social workers’ understanding of systems theories, with some empirical studies confirming the uniqueness of these understandings to social work knowledge. The theoretical literature lacks discussion regarding the distinctive nature of theories to social work, indicating either that theories are not distinctive or simply that there is a lack of literature surrounding the distinctive nature of these theories. However, literature does highlight the strength of borrowing theories from other disciplines and the benefits of adopting practices into social work knowledge.IMPLICATIONS Initial evidence suggests that systems theories may provide a foundation for defining the distinctiveness of the profession; however, further investigation is needed.Further research into how social workers epistemologically engage with systems theories may contribute to clearer articulation of their perspectives on youth mental health.Investigation into systems theories through a trauma-informed lens is required as the current literature lacks this perspective.
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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 | 0.013 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.007 | 0.044 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".