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Record W4245549232 · doi:10.24124/2016/bpgub1121

Female identity formation: relationships in Toni Morrison's novels

2016· dissertation· en· W4245549232 on OpenAlexaff
Arlinda Banaj

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicLiterary Theory and Cultural Hermeneutics
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsRomanceFriendshipPsychologyRace (biology)Identity (music)Meaning (existential)Gender studiesDevelopmental psychologySocial psychologyPsychoanalysisSociologyAestheticsArt

Abstract

fetched live from OpenAlex

This thesis uses the multiplicative approach developed by Deborah King and Patricia Hill Collins to analyze female identity formation in Toni Morrison's novels Sula, Jazz and Beloved.I focus on black women's differential experiences and the female characters' relationships with female friends, romantic partners, elders and ancestors.Female friendship is often formed through solidarity among female characters.Race plays an important role in the formation of this bond, although at times, class and gender inform the meaning of race.Through friendship, women overcome emotional pain.Without first accomplishing selffulfillment, women are not able to enter successful romantic relationships, although in certain cases, race and class change the meaning of gender and a romantic partner plays a crucial role in a female character's ability to overcome emotional trauma.Pivotal in female identity formation is also women's relationships with their elders, who, through the process of "rememoration," connect the characters to their ancestors.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.008
Scholarly communication0.0080.004
Open science0.0010.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.059
GPT teacher head0.272
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes1
Has abstractyes

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