Trinny takes all! Exploring the gendered effects of authenticity, postfeminism, and leadership on <i>The Trinny TakeOver Show</i>
Bibliographic record
Abstract
This article investigates some interconnections among postfeminism, authenticity, and leadership through an exploration of one self-proclaimed fashion entrepreneur’s use of social media to enhance their brand and their own leadership credibility. I concentrate on the fashion influencer Trinny Woodall, whose social media presence is central to the success of her company, Trinny London®. Trinny has amassed a large online following due to her confident, engaging persona. I argue that Trinny Woodall cultivates a kind of authentic persona on social media, one that is influenced by postfeminism, and intertwined with the promotion of her company. By exploring three episodes of The Trinny TakeOver Show in detail, I illustrate how she is emblematic of a postfeminist fashion influencer who uses her social media platform to create a kind of authentic connection with their followers. In making my argument, I draw together distinct literatures in cultural studies, feminist media studies, and leadership studies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".