Community Social Capital in Malaysia: A Pilot Study
Bibliographic record
Abstract
Social capital is a vital concept in identifying resources in the social network, which has the capability to be used to improve life quality and to facilitate the society development process. It emerges in the form of individual asset and needs to be analyzed through collective lifestyle or a community. An initial process has been explored to identify social capital components. The outcome is translated into an instrument comprising of six social capital components based on survey items and past studies namely participation in community activities, proactivity in the social context, neighborhood connections, multi-racial tolerance, a sense of trust and protection, and life values. A pilot study involving 41 respondents was carried out in several neighboring areas in the northern part of Malaysia. The study results show that all six components have a high internal reliability value. These components of social capital are categorized into three levels namely low, moderate and high. The findings demonstrate that the majority of the four components are at the high level. They are participation in community activities, neighborhood connections, multi-racial tolerance, and, a sense of trust and protection whereas majority of the respondents for the components of proactivity in the social context and life values is at the moderate level.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".