Bibliographic record
Abstract
“The Problem of Immigration and Contemporary Spanish Detective Fiction” examines the viability of the detective genre as a forum to dispute the commonly held perception of contemporary immigration to Spain as a problem. Focusing first on popular series of the Transition and Disenchantment periods that followed the death of Francisco Franco, I identify the detective novel, and in particular the hard-boiled variety on which the Spanish tradition is based, as an ideal space for discussions of otherness. \n\tIn the 1990s, as large-scale immigration to Spain became an increasing reality, North Africans, Latin Americans, and Eastern Europeans joined minority groups already marginalised within Spain and became the focus of well-known authors such as Jorge Martínez Reverte, Arturo Pérez-Reverte, and Andreu Martín and relative newcomers Yolanda Soler Onís, José Javier Abasolo, Lorenzo Silva, and Antonio Lozano. All use the conventions of the detective genre––suspense, pursuit, intrigue––to address misconceptions about immigration and to reveal that the ultimate culprits in these stories are ill-willed traffickers, corrupt security agencies, and the widespread apathy of parts of the Spanish population and its government. Through the twists and turns of their storylines, these politically committed authors show that while immigrants may be forced to inhabit Spain’s underbelly, they are not single-handedly responsible for Spanish society’s perceived demise. \n\tMy dissertation is informed by a multi-disciplinary approach that draws on media, cultural, socio-anthropological, and postcolonial studies. The connection between crime literature and the mass media is especially intriguing given the latter’s power of influence over the conceptualisation of immigration. The detective texts juxtapose the media of the post-modern electronic information age, which is by definition frontier-less, with a nation designing ever-stronger borders. While analysing the various borders that divide a national and global society in the entangled tale of immigration to Spain, and the discursive roles they play within the codified genre of crime fiction, I argue that these authors use the conventions of their medium to provide internal views of the process of immigration as an alternative to the voyeuristic daily reporting that otherwise threatens to desensitise the Spanish public to the topic altogether.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".