East-Indian college student’s perceptions of family strengths
Bibliographic record
Abstract
The Family Strengths Inventory (FS I), and a demographic questionnaire were distributed to 218 college students (120 women and 98 men), enrolled at a large university in Western India to determine their attitudes toward family strengths. A second objective was to determine whether ten demographic variables : age, gender, type of parental marriage, family type, parental socioeconomic status, religiosity, maternal employment, number of siblings, familial decision-making patterns, and parental marital satisfaction were related to perceived family strengths. A third objective was to determine if the six factors identified as strengths in an American sample when using the Family Strengths Inventory were the same in the Indian sample. Results indicated that three demographic variables were significantly related to family strengths: gender, type of parental marriage, and familial decision-making patterns. Factor analyses showed that five factors explained 40% of the variance in FSI scores for the Indian sample. Implications for studying Indian family strengths using the Family Strengths Inventory are discussed.
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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) | 0.001 | 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) | 0.001 | 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".