10. Here Comes Spiderman, the Arachnophobian: Halloween and Constructions of Gender
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".