Bibliographic record
Abstract
It has previously been believed that families had a negative impact in their children's eating disorders.Families were often blamed for the development and preservation of their children's eating disorders.However, within the last decade family therapy has provided evidence for the use of families in rehabilitating children with eating disorders.Additionally, families should actually not be held responsible for the development and preservation, rather viewed as patients as well.One outcome of family therapy, for patients diagnosed with an eating disorders, is the process of bringing the family unit closer together.The current literature review has two goals; first, to explore various family therapies in order to develop further understanding of eating disorders, as well as the gap and limitation within some of the current interventions.Second, is to provide possible suggestions for future research to develop other possible family interventions.Anet Mor obtained her Master in Counselling Psychology from Athabasca University in September 2017.She is currently in a supervised practice working as a mental health therapist with individuals, youth and couples in Ontario.Her interest lies in eating disorders, families who have fostered or adopted children, depression and anxiety.She is a member of the Ontario Association of Consultants, Counsellors, Psychometrists, and Psychotherapists (OACPP).
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".