The Relationship Between Years of Schooling and the Forms of Social Capital: A Study Conducted in an Urban Area, Under Sylhet City
Bibliographic record
Abstract
Education and social capital have great contribution to the development. The main endeavor of this article divulges the connection between individual’s years of schooling and their social networks, social norms, civic participation, cooperation and social trust as social capital. To find out the relationship between individual’s years of schooling and their social capital descriptive research design has been followed. Mix-method approach -- Social survey technique and Focused Group Discussion (FGD) -- has been applied for collecting data from study area. To analyze the collected data, Likert Scale, Human Development Index (HDI) and the Spearman’s rho correlation were calculated. Hypotheses have been formulated and tested in congruence with the objectives of the study. From the study, it is found that, positive relation exists between years of schooling and various components of social capital. It also signifies that, educated people have more social network and they maintain the social norms. On the contrary, they have low trust on their neighbors and are less cooperative to them too. It is also revealed, Social Networks Index is more superior over other elements of Social Capital i.e. 0.749 (social network) > 0.671 (social norms) > 0.658 (civic participation) > 0.584 (social Cooperation) > 0.425 (social trust). In conclusion, individual’s years of schooling influenced their social capital but variety of relation exists there because of the influence of others variable. Key words: Years of schooling; Social capital; Social networks; Social norms; Civic participation; Cooperation; Social trust
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.062 |
| 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".