Les préjugés raciaux et de classe dans l'œuvre de Marvel Moreno
Bibliographic record
Abstract
Ce travail d'investigation est fonde sur une analyse discursive des notions de race et de classe sociale dans la production narrative de l'ecrivaine Marvel Moreno, nee a Barranquilla. Dans un premier temps, il a ete necessaire de determiner les antecedents du sujet pour pouvoir, ensuite, elaborer un corpus de recits qui rendent compte de ces deux notions. Nous avons finalement reconstruit le code raciste et le code social de l'œuvre a travers l'etude de termes comme racisme, noir, metis, mulâtre, blanc, noir, aristocratie, decadent, bourgeois, parvenu ou nouveau riche et classe moyenne. La pertinence de cette etude est validee par l'absence, jusqu'a aujourd'hui, d'un travail qui explique, a partir de l'œuvre, de la theorie litteraire et de l'histoire colombienne, les prejuges et stereotypes au sein de la societe decrite par l'ecrivaine. D'un point de vue methodologique, nous avons analyse les opinions exprimees par les voix narratives lorsqu'elles decrivent et qualifient les personnages et les situations. Par consequent, nous avons demontre que dans l'univers fictif de l'auteure, les idees recues depuis la Colonie faconnent les modes de pensee et les relations de la haute societe de Barranquilla, societe raciste et discriminante.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".