Sex-e-Work: An Exploration on the Rise of OnlyFans as a Space for Sexually Explicit Content
Bibliographic record
Abstract
OnlyFans is a platform that has become well-known for creators selling sexually explicit content, where creators share their content with fans, often for a monthly subscription fee.Currently, little is known within an academic context about the platform and its creators of adult content.Specifically, this study sought to understand how creators experience their platform, understand their labour, and how their experiences intersect with or diverge from current understandings of sex work.To understand the lived experiences of OnlyFans creators of sexually explicit content, nine qualitative interviews and a visual content analysis of 10 creators different from those interviewed were conducted.My research illustrates how there are parallels between OnlyFans creators of sexually explicit content and other forms of sex work however, creators are experiencing sex work in new manners, particularly within a digital environment. Chapter 1: IntroductionOnlyFans is a platform that provides individuals with the opportunity to earn their income by taking a series of sexual photos, editing them, and uploading them to the Internet.With the advancement of technology, the manner in which sex or sexual content is produced, distributed, and consumed has been altered in ways that could be referred to as a new era of sexual labour.Nowadays, self-producing, sharing, and consuming sexually explicit content and porn is even easier than ever, with many individuals now capitalizing on this possibility.OnlyFans is a website platform developed in 2016, that allows individuals, known as creators, to share various content with viewers, known as their fans. 1 As explained in their mission statement, creators "monetize their content while developing authentic relationships with their fanbase." 2 OnlyFans also has a pay-per-view (PPV) feature for creators to charge their fans a fee to view a post by the creator, as well as a tipping feature.3 Through the monetization process, creators often provide an inside view of their life and persona to their fans for typically a monthly subscription fee, but creators also have the option of having a free account subscription.4 OnlyFans pays creators 80% of the money earned, while the platform retains the remaining 20%. 5 Creators on OnlyFans develop and further their relationship with their fan base by sharing content that ranges from photos to videos to writing samples, in genres such as cooking, beauty, gaming, wellness, comedy, and adult content. 6However, OnlyFans is probably best 1 "Our Team and Goals," OnlyFans, accessed June 19, 2022, https://onlyfans.com/about.html. 2 "Our Team." 3 "Community Guidelines," OnlyFans, accessed June 19, 2020, https://onlyfans.com/help.4 "Community Guidelines." 5 "Community Guidelines." 6 Alex, "Genres You Can Find on OnlyFans," OnlyFans Blog (blog).July 14, 2020, https://blog.onlyfans.com/genres-you-can-find-on-onlyfans/.within the gig economy, where creators, as independent contractors, use the platform as a supplementary or even primary source to earn income.13 OnlyFans has become well-known on social media on applications including Twitter and Tik Tok, as well as through various news articles and pop culture references, such as by Beyoncé in the Savage remix.14 OnlyFans' popularity can also be attributed to various controversies and how the platform handled them.For instance, in August 2020, former Disney Chanel star, Bella Thorne, joined OnlyFans and earned $1 million within her first 24 hours, and $2 million shortly after, causing creators who were on the platform prior to Thorne to be upset, as she was an already wealthy celebrity entering the space of largely non-celebrities and taking away from their potential fans and income.15 The outrage grew when Thorne promised nude photos for $200 through the PPV feature, but after subscribers did not receive the promised content, they sought a refund.16 OnlyFans then announced various changes to the website, claiming it was unrelated to Thorne, although creators suggest otherwise.17 OnlyFans placed a $100 cap on PPV messages and a $50 cap on PPV posts for creators who offer a free account.18 Both PPV options had a cap of $200 previously.19 OnlyFans also changed the tipping limit for new users to $100 but allows Quota, April 7, 2021, https://thenorthernquota.org/news/students-are-turning-onlyfans-site-make-money-during- pandemic; Andrew Court, "1 in 5 People Considering OnlyFans to Afford Living in NYC -As Rents Skyrocket," New York Post, March 9, 2022, https://nypost.com/2022/03/09/1-in-5-people-considering-onlyfans-to-afford-living- in-nyc-as-rents-skyrocket/; Griffin Wynne, "OnlyFans Helped Me Pay Off the Last of My Student Loans," Bustle, April 15, 2021, https://www.bustle.com/life/only-fans-pay-off-student-loans.13 Aryana Safaee, "Sex, Love, and OnlyFans: How the Gig Economy Is Transforming Online Sex Work" (master's Thesis, San Diego State University, 2021), 1-97, https://digitallibrary.sdsu.edu/islandora/object/sdsu%3A139760.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".