More than an outcome: a person-centered, ecological framework for eating disorder recovery
Bibliographic record
Abstract
BACKGROUND: Eating disorder recovery is a complex phenomenon. While historical understandings focused on weight and behaviours, the importance of psychological factors is now widely recognized. It is also generally accepted that recovery is a non-linear process and is impacted by external factors. Recent research suggests a significant impact of systems of oppression, though these have not yet been named in models of recovery. BODY: In this paper, we propose a research-informed, person-centered, and ecological framework of recovery. We suggest that there are two foundational tenets of recovery which apply broadly across experiences: recovery is non-linear and ongoing and there is no one way to do recovery. In the context of these tenets, our framework considers individual changes in recovery as determined by and dependent on external/personal factors and broader systems of privilege. Recovery cannot be determined by looking solely at an individual's level of functioning; one must also consider the broader context of their life in which changes are being made. To conclude, we describe the applicability of the proposed framework and offer practical considerations for incorporating this framework in research, clinical, and advocacy settings.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.036 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.012 | 0.027 |
| Insufficient payload (model declined to judge) | 0.003 | 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".