The Censorship of Sex: A Study of Raymond Chandl er’s The Big Sleep in Franco’s Spain
Bibliographic record
Abstract
During the period when General Francisco Franco ruled Spain (1936-1975), official censorship kept a watch on all books that were published in the country. The main objective of this censorship was to conceal from the Spanish people political manifestations that might be ultimately threatening for the dictatorial government politically. However, under heavy influence of the Catholic Church, the censors also veiled for the moral health of the Spanish people by intervening in all matters of sexual morality, decency, obscenity and vulgarity. Research has shown that during this period censors were as vigilant for sexual content as they were vigilant for political content. In this study I will examine censorship and sex by studying Raymond Chandler’s first novel, The Big Sleep (1939) and the three Spanish-language translations published during this period (1949, 1958, 1972). Chandler’s novel contains no potential political offenses to Franco’s Regime and its allies, but it does contain references to male homosexuals, scenes of female nudity, and sexually suggestive dialogues involving the detective and a female character. All of the Spanish versions were censored, whether by government censors or the translators/editors prior to presenting the manuscript to the censors. I will discuss the government-censored and self-censored passages in the Spanish versions of the novel, and show that all of the references to the homosexual characters, much of the nudity, and many of the sexually-suggestive dialogues have been manipulated and/or suppressed, producing undesirable and often unexpected effects.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".