Surveillance culture and ethnically diverse adolescent bodies in Anglophone young adult fiction
Bibliographic record
Abstract
The body has historically been the site of ‘contestation’ (Boudreau 6-7) for Western sociologists, feminist literary critics and cultural theorists, playing a constantly evolving role in identity and liberation movements. As such, it should now be considered in relation to a culture of surveillance. The engagement in and with social surveillance practices and imaginaries, as Lyon attests, ‘prompts normative and ethical questions’ (‘Digital Surveillance’ 836).Traditionally, research evidences theoretical inquiry that centralises the body (for example, in works by prominent feminists such as Butler, Grosz and Bordo) and places particular emphasis on the correlation between physical appearance, alteration and the development of female subjective agency. Adolescent bodies have been theorised, particularly by Young Adult (YA)Fiction scholars such as Trites and Younger, as sites of social and cultural inscription. Mirroring Western society, Anglophone YA Fiction typically privileges male, White teenage characters over adolescents from diverse cultural backgrounds as central protagonists, narrators or focalisers, preferencing Anglonormative portrayals of Western adolescence and White social mobility. A substantive challenge to this approach is currently being presented by an emerging group of contemporary female and Asian YA authors writing in English in Australia, Canada and America. Authors publishing works between 2004 and 2017 (such as An Na, Suzanne Kamata, Randa Abdel-Fattah, S.K. Ali, Mariko Tamaki, Keshni Kashyap, G. Willow Wilson) explicitly attempt to interrogate ways in which the female Asian adolescent body experienced pre-Covid surveillance practices. Each author disrupts patriarchal, Anglonormative depictions of adolescence by writing from the perspectives of female Asian second-generation migrants and refugees. This thesis explores how their work shifts and modifies the picture of young adolescent bodies seen in Anglophone YA Fiction and addresses a gap in 21st-century YA scholarship informed by ethnically diverse perspectives of publicly and digitally surveilled adolescent female bodies.
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 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 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".