SEX AND AGGRESSION IN NELSON Mc CORMICK’s PROM NIGHT \nMOVIE (2008); A PSYCHOANALYTIC CRITICISM
Bibliographic record
Abstract
Febriasari Ratna Wulan. A320070309. SEX AND AGGRESSION IN NELSON Mc CORMICK’s PROM NIGHT MOVIE (2008); A PSYCHOANALYTIC CRITICISM. Research Paper. Muhammadiyah University of Surakarta. 2011. \n The major problem in this study is to show sex and aggression in Nelson Mc Cormick’s Prom Night movie by using psychoanalytic criticism. It is conducted \nby analyzing the movie based on its structural elements and based on psychoanalytic criticism. \n This research is qualitative research. Type of data of the study is text and image taken from two data sources: primary and secondary. The primary data \nsource is Prom Night movie directed by Nelson Mc Cormick released in 2008. While the secondary data sources are taken from the books of literary, internet, and other relevant information. Both data are collected through library research and analyzed by descriptive analysis. \nUsing a psychoanalytic criticism as the theoretical framework, the research shows the following findings. First, based on the structural analysis it seems that \nin this movie, Nelson Mc Cornmick delivers a message about unnatural obsession can cause negative ability until make an aggression to another people. Second, \nbased on psychoanalytic analysis, Nelson wants to convey the psychological phenomena that is a type of personality that leads to sex and aggression \n
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".