Ellie Tomsett: <i>Stand-up Comedy and Contemporary Feminisms: Sexism, Stereotypes and Structural Inequalities</i>
Bibliographic record
Abstract
Stand-Up Comedy and Contemporary Feminisms: Sexism, Stereotypes and StructuralInequalities is an in-depth look at women and feminism in stand-up comedy in the United Kingdom.The book takes an intersectional feminist approach to the study of comedy and importantly, states that this approach is inclusive of all women.In a political climate that is increasingly hostile towards transgender women, author Ellie Tomsett's assertion is, sadly, a welcome and necessary one.But, as Tomsett is the first to admit, women in the UK comedy scene are still primarily cisgender and white.Because of this, the inclusion of a diversity of voices can sometimes be limited.Again, this is something the book acknowledges and actively tries to correct as evidenced in Chapter 4's discussion of the additional harassment that women of color face online (misogynoir) and the ableism of comedy venues.From discussing the historical roots of comedy in the UK to the rise of alt-right, incel, and TERF culture, this book argues that to fully explore feminism and comedy, it is important to address the political, economic, and social context in which it arises and operates within.Stand-Up Comedy and Contemporary Feminisms does an excellent job of unpacking the implications of policies and practices that, while on the surface may not appear to be gendered, have a great impact on the lived experiences of women in comedy.For example, while the lack of funding for individual comedians in the UK might appear like a gender-neutral problem, Tomsett illustrates how it disproportionately impacts women who are already marginalized in the industry.Tomsett's dedication to women in comedy is apparent in every aspect of the book including its methodology.As Tomsett argues, comedy research still tends to "foreground analysis of the content and performance style of comedy" (p.3), without considering how comedy is created and the ways audience receive it.While Tomsett analyzes women's comedy routines (both feminist and postfeminist), she also includes rich information collected from her time as a participant-observer at the UK Women in Comedy festival, interviews with both comedians and comedy audience members, and even presents her own forms of policy-driven activism.Tomsett's use of multiple methodologies lends a personal richness to the text that demonstrates a deep-felt trust between researcher and research-participants.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".