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Record W4248510425 · doi:10.24908/iqurcp.8796

10. Here Comes Spiderman, the Arachnophobian: Halloween and Constructions of Gender

2016· article· en· W4248510425 on OpenAlexvenueno aff
Angela Nemec

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
Fundersnot available
KeywordsHeteronormativityGender studiesSociologyHuman sexualityCritical discourse analysisThe SymbolicHegemonyDeviance (statistics)AestheticsPsychologyPsychoanalysisArtLawIdeology

Abstract

fetched live from OpenAlex

Holidays are celebrations, symbolism, and cultural traditions combined. Halloween allows for individuals, for one night a year, to transform themselves and enter a fantasy world (Kugelmass, 1994). However, upon further critical examination, this rhetoric of Halloween as a harmless, imaginative, and liberating experience undermines the critical reflection of the negative impact of many of the Halloween traditions. The Halloween ritual perpetuates social constructions of gender, which reflects society’s gender inequality and heteronormativity. During Halloween celebration, exaggerated gender stereotyping is acceptable and is thus reinforcing these norms without critical examination. Themes, paraphernalia, rituals, and costumes, under labels such as ‘Halloween’, ‘tradition’, or ‘holiday’ are symbolic and hold much power. This research seeks to deconstruct these meanings in order to argue the effects they have on the reproduction of gender norms and stereotypes as well as heteronormativity. Halloween has a lot to do with visual representation. Often, this visual representation during Halloween celebration “…reproduces and reiterates more conventional messages about gender (Nelson, 2000). In the process of ‘celebration’, these messages about gender are given the opportunity to manifest themselves. Rarely do those partaking in these rituals critically examine the broader implications to gender stereotyping and inequality as well as heteronormativity and homophobia. Areas of study that will be discussed in the process of arguing these statements include gender (norms, roles, stereotypes, deviance, and sexuality), media, culture, consumerism, fashion, celebrations, and rituals.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.006
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.157
GPT teacher head0.397
Teacher spread0.240 · 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 designTheoretical or conceptual
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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