Reflexivity in the Everyday Lives and Work of Refugees and Therapists
Bibliographic record
Abstract
In this chapter we (two systemic psychotherapists) write about our work with refugees and asylum seekers in which we aim to help rekindle trust and find a way of living on in a social world often without political protection. This context poses particular challenges to therapists, because for refugees and asylum seekers ordinary everyday events point to extraordinary ruptures and violations in the past. Drawing on the idea of Veena Das of ‘the everyday work of repair’ and on her use of Wittgenstein’s notion of ‘turning back’, we argue that these ideas are useful in understanding how violent ruptures, betrayal, displacement and loss may be revisited so that persons can go on living with these experiences, not in the past but in the present, without erasing the past and at the same time keeping the potentiality of the future. Using examples, we show how we enter this territory through the use of our understanding of what we call ‘the human condition’ and our own reflexivity.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.049 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".