TEACHING POSTMODERN AND NARRATIVE SOCIAL WORK PRACTICE THROUGH THE USE OF FILM-BASED CLIENTS
Bibliographic record
Abstract
This paper elaborates on the use of film-based clients in teaching narrative therapy in social work. In this paper, I provide my rationale for the use of film-based clients and then highlight the life story of Lars, taken from the film Lars and the Real Girl (2007), as an example of how film clients can be a helpful way of learning how to practice narrative therapy. The theory and epistemology of narrative therapy—and specifically a postmodern approach to the central organizing concepts of story, experience, self, knowledge, and power—are discussed. I then illustrate key elements of narrative practice with Lars as a film-based client. The attention to creating counternarratives challenges dominant social discourses in Lars’ story about mental health and coping with difficult life events, and the internalization of these ideas as part of the story of his identity. A positioned approach against the medicalization and pathologization of Lars’ struggles reflects the social justice commitment of narrative practice.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".