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Record W4401628917 · doi:10.22215/etd/2024-16097

"They Called Me Wonder Woman": Identifications and Representations in Wonder Woman Media

2024· dissertation· en· W4401628917 on OpenAlexaff
Shoshana Rosa Cohen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsWonderCharacter (mathematics)AestheticsArtMedia studiesPsychologySociologySocial psychologyMathematics

Abstract

fetched live from OpenAlex

Wonder Woman was originally created as feminist propaganda, but there remains controversy over whether she truly represents feminist values. Many researchers have tried to settle the question by examining Wonder Woman media, but few have explored the role Wonder Woman plays in the lives and identities of fans. To accomplish this task, a survey was designed to ask participants about their experiences interacting with Wonder Woman media. The results showed that fans actively use their favorite versions of Wonder Woman to create their own model of her ethical principles, while dismissing versions of the character that they feel are not in keeping with her “true” character. Audiences identify with Wonder Woman, and bring her character traits and values into their daily lives. Audiences are inspired by Wonder Woman to aim higher, to improve their own character, and to act with greater love and tolerance, especially towards gender and sexual minorities.

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)0.007
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 score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.008
Scholarly communication0.0060.006
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.369
Teacher spread0.330 · 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
Published2024
Admission routes1
Has abstractyes

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