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Record W7056185081

Educational Gothic: Interrogating Violent Educations inAustralian, Canadian and United States Fictions 1960-present

2024· other· en· W7056185081 on OpenAlexaboutno aff

Bibliographic record

VenueNottingham ePrints (University of Nottingham) · 2024
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)IndigenousColonialismRepresentation (politics)InstitutionFoundation (evidence)Educational institution
DOInot available

Abstract

fetched live from OpenAlex

My thesis examines depictions of education within bildungsroman-style Gothic novels and films produced in the United States, Australia, and Canada. I coin the label “Educational Gothic” to define these works. The shared context of settler colonialism is the critical foundation for my comparative analysis. If the bildungsroman has been central to burgeoning settler nations in solidifying a national character and establishing a sense of tradition, I examine its reverse in the Educational Gothic mode. I theorise that the Gothic institution reoccurs as a means of depicting and interrogating violent educational histories within these three nations, particularly when they are not present within official rhetoric. However, the relationship between history and representation is never clear-cut, and creates dynamic instabilities within creative productions. Thus, from 1960 to the present, this thesis charts the emergence and development of the Educational Gothic mode in film and literature, exploring how authors respond to the socio-political climate and examine identity, history and tradition through educational narratives. I delineate two strands of the Educational Gothic mode, Settler and Indigenous, and pay close attention to how these creatives respond to genocidal settler-colonial educational policies towards Indigenous peoples and women’s educational experiences in patriarchal institutions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.431
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.2510.001

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.

Opus teacher head0.017
GPT teacher head0.265
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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