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Record W4297893635 · doi:10.24124/2022/59315

The Grey: Emerging identity of the female androgynous hero

2022· dissertation· en· W4297893635 on OpenAlexaff
Alora Bowness

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsHEROFemininityIdentity (music)ArchetypeMasculinityIdeologyAestheticsGender studiesLiteratureSociologyArtPoliticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Theorists who study the formulation of the hero have identified that the appearance of the hero varies depending on the time and place they are needed. Yet, the function of hero archetypes, such as Joseph Campbell’s monomyth, have reinforced traditional Caucasian masculine male mythic ideologies in young-adult fiction. Reconfiguring the idea of the hero to question its masculine bias and include a female androgynous heroic paradigm will expand the limited classification of “hero” as the hero is encouraged to hone both her masculinity and femininity. This project focuses on a hero with both an androgynous personality and an Indigenous heritage. These aspects of my project push back against the gender and cultural norms often associated with heroic journeys in Western culture. Throughout this thesis, I formulate a more accepting form of identity by mapping an encompassing version of the hero’s journey that pushes the boundaries of classic “heroism” but still utilizes the familiar and effective pattern of the heroic journey of the self by comfortably living in the what I am titling “grey space”. By illustrating the fluidity of identity, young readers can relate to a heroic character who encompasses more than the traditional role outlined by Campbell.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.996

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.355
Teacher spread0.318 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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