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Record W3127563984 · doi:10.29173/cons29437

Phrenology and Autodiegetic Narration in Jane Eyre

2021· article· en· W3127563984 on OpenAlexaffvenue
Shelby Elizabeth Haber

Bibliographic record

VenueConstellations · 2021
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhrenologyNarrativeParallelsContext (archaeology)Representation (politics)TRACE (psycholinguistics)LiteraturePsychoanalysisHistoryPsychologyAestheticsArtPhilosophyPoliticsLaw

Abstract

fetched live from OpenAlex

This paper examines how Charlotte Brontë's belief in phrenology influences the narration of her novel Jane Eyre. Phrenology was a nineteenth-century belief that the shape of the skull could give information about a person's temperament. Phrenologists speculated that the brain was split into separate parts, or faculties, that defined the individual's ability to feel a particular emotion. A bump on the skull implied that the faculty underneath that part of the skull was bigger, so the individual was more inclined to feel that emotion. By placing Jane Eyre within the historical context of the rise of phrenology, I explore the ways in which Brontë's phrenological representation of Jane's mind informs and parallels the autodiegetic narration of Jane Eyre. My analysis focuses on moments when Jane draws attention to the fact that she is a first-person narrator telling the story of her own past experiences. I argue that these moments are comparable to those when Jane’s experiencing-self is fractured into phrenological faculties. Concomitantly, I seek to trace how Jane's narration changes as she moves between the locations of Thornfield, the Moor House, and Ferndean. I suggest that the shifts in narration draw attention to these locations as metaphors for varying degrees of restriction on Jane's faculties. Through an application of nineteenth-century psychological studies, I conclude that Brontë uses her narration style to criticize phrenologists who promote an unnaturally restrictive control of the faculties.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.024
GPT teacher head0.294
Teacher spread0.270 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2021
Admission routes2
Has abstractyes

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