Shame and Eviction in Juan Miguel del Castillo’s <i>Techo y comida</i> (2015)
Bibliographic record
Abstract
In 2014, Spain’s then prime minister Mariano Rajoy declared: ‘La crisis ya es historia’. This proclamation of recovery was based solely on macro-economic indicators and reinforced a flawed hegemonic narrative equating progress with economic growth. It ignored what Labrador Méndez calls ‘historias de vida subprime’: subjective and affective accounts of the enduring eviction crisis triggered by the 2008 financial meltdown and strict austerity measures. Juan Miguel del Castillo’s film Techo y comida is one such ‘subprime’ life story. It follows Rocío, a young, unemployed, single mother facing eviction from her rental property in the absence of state or community support.Exposing the flipside to the Rajoy’s statistics, the film reveals the increasingly brutal ‘expulsions’ (Sassen) that facilitate GDP recuperation. It politicizes through affect, showing that shame functions as a mechanism for social exclusion and normalisation but also as a catalyst for altruism. Within the diegesis, Del Castillo uncovers the potent, subjective shame that conceals expulsions and allows them to proliferate. This concurrently engenders shame in the spectator, encouraging them to consider their part in sustaining these degrading processes at micro-level and pointing them towards ‘non-capitalist practices’ (Castells et al).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| 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".