Antonella: ‘A Stranger in the Family’—A Case Study of Eating Disorders Across Cultures
Bibliographic record
Abstract
Abstract The story of Antonella illustrates the way in which cultural and other values impact on the presentation and treatment of eating disorders. Displaced from her European home culture to live in Canada, Antonella presents with an eating disorder and a fluctuating tableau of anxiety and mood symptoms linked to her lack of a sense of identity. These arose against a background of her adoption as a foundling child in Italy and her attachment problems with her adoptive family generating chronically unfixed and unstable identities, resulting in her cross-cultural marriage as both flight and refuge followed by intense conflicts. Her predicament is resolved only when after an extended period in cultural family therapy she establishes a deep cross-species identification by becoming a breeder of husky dogs. The wider implications of Antonella’s story for understanding the relationship between cultural values and mental health are briefly considered.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".