The Relationship between Affective and Social Isolation among Undergraduate Students
Bibliographic record
Abstract
We examined the correlation between social isolation and affective isolation among 457 undergraduate students using a stratified cluster sampling technique. Participants comprised 221 men and 236 women, all of whom were either first- or fourth-year students enrolled in various majors at King Saud University. Means, standard deviations, Pearson (Spearman) correlations, z-values, a regression analysis, and an analysis of variance were used to address the study questions: (Are there significant differences (α ≤ .05) in affective isolation per sex and academic level? Does the interaction between sex and academic level have a significant impact on affective isolation? What is the nature of the relationship between affective isolation and overall social isolation and its dimensions? Are there significant differences (α = .05) in the relationship per sex and academic level? Does affective isolation contribute towards the prediction of social isolation?). Significant differences regarding sex were found, as men showed more affective isolation. Significant differences were also found regarding the interaction between sex and academic level on affective isolation. However, the correlations between the social isolation dimensions of self-confidence, family containment and communication, and interaction with friends with affective isolation were negative. In addition, affective isolation predicted social isolation among students.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".