PENDEKATAN SISTEMATIS DALAM PENILAIAN DAN INTERVENSI KELUARGA: TINJAUAN LITERATUR TERHADAP CALGARY FAMILY ASSESSMENT AND INTERVENTION MODEL (CFAM/CFIM)
Bibliographic record
Abstract
Tinjauan literatur ini bertujuan untuk mengeksplorasi Calgary Family Assessment and Intervention Model (CFAM/CFIM) dalam hal penilaian dan intervensi keluarga. Pencarian dilakukan pada database Google Scholar, PubMed, dan ScienceDirect dengan kata kunci "Calgary Family Assessment Model", "Calgary Family Intervention Model", "penilaian keluarga", "intervensi keluarga", dan "keluarga". Sebanyak 10 artikel ditemukan dan dianalisis. Hasil menunjukkan bahwa CFAM/CFIM adalah model intervensi keluarga yang sistematis dan berpusat pada keluarga yang terbukti efektif dalam meningkatkan hasil bagi keluarga, termasuk peningkatan kesehatan mental, fungsi keluarga, dan kualitas hidup. CFAM menyediakan kerangka kerja yang komprehensif untuk menilai keluarga, dan CFIM menawarkan berbagai strategi intervensi yang dapat disesuaikan dengan kebutuhan individu dan keluarga.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".