POTRET MASYARAKAT URBAN DALAM NOVEL RESIGN KARYA ALMIRA BASTARI
Bibliographic record
Abstract
This study aims to: (1) describe the description of the prestige of urban recreation in Almira Bastari's Resign novel; (2) describe the description of the instant life culture of urban communities in Almira Bastari's Resign; (3) describe the description of the virtual lifestyle of urban communities in Almira Bastari's Resign; (4) describe the description of the individualist lifestyle of urban society in Almira Bastari's Resign novel. This type of research is qualitative research using descriptive methods. Based on the results of data analysis obtained; (1) the recreational prestige of urban community leaders in Almira Bastari's Resign includes education, employment, entertainment venues visited, and restaurants visited; (2) the instant life culture of urban communities depicted in Almira's Resign in general coming to fast food restaurants; (3) the individualist lifestyle of urban society in Almira Bastari's Resign as if it had never been separated from technology and communication in everyday life. Urban communities rely on information and communication technology to seek information, communicate, and obtain entertainment; (4) a portrait of the lifestyle of the individual urban society in Almira Bastari's Resign, like to do everything by yourself and some people prefer to live without the interference of othersKeywords: urban society, Resign novel, Almira Bastari
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".