Urdu Translation of the California Inventory for Family Assessment for Use in Pakistan
Bibliographic record
Abstract
In the absence of indigenously developed valid measures to study constructs related to marriage and family in Pakistan, the most economical way is to translate and adapt an instrument that has already been validated in other cultures. The purpose of this study was to translate into Urdu language and pilot test a measure of dyadic relationship behavior, the California Inventory for Family Assessment (CIFA; Werner & Green, 1999-2008). Brislin’s (1970) back translation method was employed. Our translation/backtranslation process is summarized in detail. Face validity and content validity were addressed by use of a committee of judges as well as by interviewing and pilot testing on 15 married couples. The translated version proved to be equivalent to the original version in semantic, idiomatic, experiential and conceptual domains. Cronbach’s alpha reliability coefficients as well as inter-spouse validity correlations indicate that most constructs measured by CIFA were applicable in the cultural context of Pakistan. However, subscales with weak reliability and validity results in the pilot study need to be explored further to better understand their suitability for research in Pakistan.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".