Bibliographic record
Abstract
espanolFrecuentemente, la obra de Stanley Kubrick ha sido estudiada desde cuestiones formales o tematicas que rara vez han permitido la entrada a aspectos narrativos. Este articulo analiza la construccion del personaje protagonista desde la concepcion psicologica el mismo, evaluandolo como plano o redondo. Nos atendremos a los referentes previos literarios y narratologicos en el estudio de la dimensionalidad del personaje desde estos criterios. El objetivo sera apreciar el posible uso del personaje como categoria narrativa capaz de otorgar unidad a la obra de un director, convertido asi dicho uso en rasgo estilistico. Veremos que la frecuente activacion de estereotipos en la filmografia de Kubrick procedera del habitual recurso a los generos puros y a los estereotipos asociados a estos, subordinados a objetivos de mayor ambicion intelectual o ideologica EnglishOften the work of Stanley Kubrick has been considered from formal or thematic researches that didn�t almost analyze the narrative creation. This article analyzes the making of the main character as a psychological construction, evaluating his dimensionality as flat or round. We�ll focus on the previous literary and narratologic references in the study of the character�s dimensionality from these criteria. The aim will be to detect the possible use of character as a narrative category able to conform unity in the work of the director, as an stylistic feature. We´ll see that the usual resource to stereotypes in Kubrick's movies will come from the resource to pure genres and to stereotypes associated with these, subordinated to objectives of more intellectual or ideological ambition
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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 | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".