Haunted World-Ecologies And Collapsed Environments In Contemporary Haunted Houses Across The Americas
Bibliographic record
Abstract
This thesis proposes an expansion of ecocriticism and Ecogothic studies into oiko-criticism and oiko-gothic studies. Thus, it proposes to read haunted houses across the Americas as haunting manifestations of Jason Moore’s oikeios, which refers to the bundles of co-production between agents that make the web of life. Through its haunting reclamation of agency, the haunted oikeios deranges then the Capitalist world-ecology, and its capacity of reproducing environments organized by Cartesian binaries and therefore exploitable subjects. The first chapter compares the haunting oikeios of La casa lobo (dirs. Cristóbal León and Joaquín Cociña, 2018), a Chilean stop-motion animation film, and the United States novel House of Leaves (Mark Z. Danielewski, 2000). In it, I propose to expand Esther Pereen’s concept of the living ghost of the disappeared to the realm of what the world-ecology has deemed as extra-human nature. For both cases, the excess of disappeared land comes back to haunt the world-ecology to reclaim its agency within the haunted oikeios. The second chapter compares the Argentinian novel Bestias afuera (Siccardi, 2013), and the Canadian-Mexican novel Mexican Gothic (Moreno-Garcia, 2020). In it, I augment Pereen’s use of the spooky medium into the haunted house and its estate to explore how it creates haunted geographies and reveals the haunted oikeios, which nullifies the Capitalist fantasy of what Moore understands as ecological revolutions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| 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".