Peran Struktur Sosial dalam Pembangunan Sarana Prasarana Permukiman Perkotaan (Studi Kasus: PLPBK Kelurahan Karangwaru Kecamatan Tegalrejo Kota Yogyakarta)
Bibliographic record
Abstract
Social structure is one of the important elements in development. Elements in the social structure will form relationships and form joint actions on the program. PLPBK Program in Karangwaru Village, Tegalrejo Sub-District, Yogyakarta City has focus on society. Social life is closely related to social structure. Based on the explanation, the purpose of this research is to determine the role of social structure in the PLPBK program in Karangwaru Village. The approach of this research is deductive qualitative. The method of analysis used is descriptive qualitative. Methods of data collection using field observation, secondary survey, and primary survey. Sampling technique of primary survey using non-probability sampling that is purposive sampling. The results showed that the social structure in Karangwaru Village has a positive and negative role in the PLPBK program. Social institutions, social groups, power and authority, and culture have a positive role while social stratification and social dynamics have a positive and negative role. The function of social structures such as maintaining patterns, integration, achieving objectives, and adaptation has been demonstrated by the social structure in the PLPBK program at Karangwaru Village.Keywords: Development; Infrastructure; Social Structure; Society
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".