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Record W7132958946

Creative Becomings: Explicit Fanfiction, Reinventing Adolescence, and Queer Relationality

2022· dissertation· W7132958946 on OpenAlexaff
Angela Fazekas

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsWomen's and Gender Studies et Recherches Féministes
Fundersnot available
KeywordsFandomQueerHuman sexualityMoral panicNarrativeTransgenderGenerative grammarQueer theoryYouth culture
DOInot available

Abstract

fetched live from OpenAlex

This dissertation is an interdisciplinary study into the experiences of adolescent fans in online fan spaces, particularly as they interact with sexually explicit fanfiction. Drawing together the threads of queer theory, adolescent sexuality, critical race theory, and fan studies, I use debates about teenagers and access to pornographic fanfiction as a starting point for a wider consideration of queer adolescent fans, the generative capacity of fan creative writing, particularly of the pornographic sort, and the relationality between adult and teenage fans. Working from Jen Gilbert’s (2007) provocation that “rather than trying to extricate youth from risk, for adolescence to occur, a risk must be taken ... tolerating this view of adolescence as development will require something more of adults and sex educators: the risk of relationality” (50), I explore sexually explicit fanfiction written and read by teenagers which puts adults and adolescents into direct conversations about desire and sexuality. Given the moral panics about teenagers accessing sexual information and engaging with sexual narratives online, as well as discourses that cast any adult engaging in conversations about sexuality with teenagers outside of an institutional setting as inherently predatory, I question what fandom and sexually explicit fanfiction might offer us in terms of alternative forms of “growing up” and relationality outside of the discourses of protection and education. I thus draw on theories of storytelling, play, digital space, and sideways growth to explore how/if fandom can offer a more generative way of looking at teenage experiences in the digital realm. Working from an understanding of fanfiction as collective, intertextual, and generative storytelling, each chapter of my dissertation involves discourse analysis and a close reading of a mix of fan-generated texts, from fanfiction (including some of my own early writing) to the debates, discussions, and creative engagements with fanfiction stories on the Archive of Our Own, Tumblr, and Twitter. In looking beyond moral panics, and the dual impulses to educate and to protect, I seek to consider what kind of creative work teenagers can generate and what this work can do – both for teenagers and for adults who interact with them.

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)0.005
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 score0.011
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.026
Scholarly communication0.0100.009
Open science0.0010.008
Research integrity0.0010.004
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 head0.027
GPT teacher head0.365
Teacher spread0.338 · 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
Published2022
Admission routes1
Has abstractyes

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