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Record W2338971108 · doi:10.3167/hrrh.2016.420107

Objectification, Empowerment, and the Male Gaze in the Lanval Corpus

2016· article· en· W2338971108 on OpenAlexvenueno aff
Elizabeth S. Leet

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsGazeMirroringObjectificationEmpowermentMale gazePsychologyStyle (visual arts)Social psychologyAestheticsSociologyGender studiesVisual artsArtPsychoanalysisPolitical scienceLaw

Abstract

fetched live from OpenAlex

Each tale in the Lanval corpus revolves around fairy women who style their bodies specifically to attract the male gaze. Each fairy uses her body’s visual impact to seduce her lover and resolve the judicial accusations against him. By adapting her body for private audiences, public parades, and even non-noble onlookers, each fairy participates actively in the gaze both to gain her respective lover’s freedom and to win the man of her choosing. The Lanval tales reveal women who submit to be analyzed and objectified in order to satisfy their lover’s wish along with their own goals. Additionally, Sir Landevale and Sir Launfal expand descriptions of the ladies, mirroring the increase in the number of people who assess them at the Arthurian trial. By examining the increasing volume of attire and decreasing interaction with animals across the adaptations, we see these poets problematize the overlap between objectification and empowerment.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0070.011
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.082
GPT teacher head0.424
Teacher spread0.342 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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