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Record W7132963216

From the Light into the Dark: Understanding Transgressed Spatial Boundaries in Are You Afraid of the Dark?

2019· article· en· W7132963216 on OpenAlexaboutno aff

Bibliographic record

VenueLehigh Preserve · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTelevision seriesMidnightConversationNightmareCultOrder (exchange)
DOInot available

Abstract

fetched live from OpenAlex

\u0026lt;p\u0026gt;On October 31, 1990, the first episode of the children's television series Are You Afraid of the Dark? aired on the Canadian station Youth Television (YTV). The series, which would be comprised of 91 episodes and 7 seasons, began with the phrase, "Submitted for the approval of the Midnight Society. I call this story…" (MacHale). The opening campfire scenes and the stories that followed strike at the heart of nostalgia for many horror fans. The series has maintained a sizeable cult following that continues to enjoy the show's tales of horror, science fiction, and fantasy. Its influence and success precedes youth-oriented horror anthologies like Tales from the Crypt Keeper (1993), The Nightmare Room (2001), Goosebumps (1995), and R.L. Stine's The Haunting Hour (2010). In this work, I begin a conversation regarding Are You Afraid? and the efficacy of young adult horror, in order to apply a critical lens to a series that targets a young, developing audience. Moreover, I argue the significance of spatial boundaries, the consequences of transgressing borders, and the importance of morally ambiguous messaging to a young audience. By addressing these elements, we can understand the didactic lessons of adolescent horror, address concerns regarding suitable content for developing viewers, and learn about young audience's consumption of horrific material.\u0026lt;/p\u0026gt;

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)0.006
metaresearch head score (Gemma)0.008
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 score0.031
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0160.054
Scholarly communication0.0150.013
Open science0.0020.009
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.023
GPT teacher head0.268
Teacher spread0.245 · 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
Published2019
Admission routes1
Has abstractyes

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