Calgary assessment model: study of family units with child malnutrition
Bibliographic record
Abstract
To describe the experience of using the Calgary Family Assessment Model in two family units with child malnutrition, as well as to construct their genogram and ecomap, analyzing the profile of the family structure. This is a case study carried out with two families, with a qualitative approach, developed in a reference unit for early childhood care, located in the city of Fortaleza-CE, from March to May 2023. ethical assessment with CAAE 66662422.8.0000.5049. Family 2 presented a higher risk of food insecurity, since only one of its components (F1) is the breadwinner. In addition, it was found that the therapies used in nutritional monitoring achieved greater adherence in Family 1, correlated with greater access to food, as well as the higher level of education of its members. However, through the application of the Calgary Model of Family Assessment, one can recognize the ability of families to solve problems, as well as inhibitions related to the educational nature that make it difficult to adhere to the interventions offered about child malnutrition.
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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) | 0.000 | 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 | 0.000 |
| 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".