Focusing on reality TV: exploring women's participation in talent-based competition shows
Bibliographic record
Abstract
Reality TV has become a source of entertainment as well as scorn for North American audiences and critics.While American reality TV and their contestants have received much attention in media studies, very little has been written about Canadian reality show participants, despite the popularity of this type of programming in Canada.Women on both sides of the border who participate on reality TV are particularly scrutinized and those with high public profiles have faced an overwhelmingly negative backlash.Using a feminist cultural studies framework, this dissertation examines Canadian women's motivations and understanding of the reality TV process, from audition to post-show life.A total of 14 women from across Canada, who competed in such shows as Canada's Next Top Model, Canadian Idol, Project Runway Canada, So You Think You Can Dance Canada, Rock Star: INXS, and Popstars: Boy Meets Girl, were interviewed using a combination of online and in-person interviews.The women's narratives of reality TV participation reflect and extend contemporary scholarly concerns and debates about women and celebrity culture, media power, television audiences, and new media technologies.Specifically, the interviews complicate current assertions and assumptions about women's participation as either 'empowering' or 'victimizing' by illustrating how such participation cannot be isolated from economic factors and gender dynamics at play in contemporary models of television production.While the women have little to no control over how they are represented in these shows, they find ways to assert their agency that disrupts (but does not stop) the production process, while simultaneously 'domesticating' the space of reality TV in order to make it a habitable and liveable place.Finally, this dissertation makes two major methodological interventions into the study of television.Firstly, using a cultural studies approach to television research, the author understands reality show contestants as a distinct category of research respondents who challenge and blur rigid divisions between audience and text, and audience and producer.Secondly, the author draws on the tradition of self-reflexivity in feminist research in order to examine and theorize to what extent the interview process may position the researcher as a 'scholar-fan'.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".