‘Sexting’: the exchange of sexual messages online among European youth
Bibliographic record
Abstract
Sexting’: a new cultural phenomenon? School boards are grappling with a vexing problem – how to curb proliferation of sexually explicit texts and photos sent between teens. ( Toronto Sun , 24 March 2011) A dangerous “sexting” trend seems to be on the rise among minors after six teenagers were probed by police over explicit images sent over the web or mobile phones, police said. ( The Sydney Morning Herald , 22 March 2011) The invention of a new term – for example, the portmanteau integration of sex and texting into the concept ‘sexting’ – may or may not identify a new phenomenon. Despite the public attention attracted by media announcements, such as those that open this chapter, it is unclear whether sexting is new and problematic or merely the latest moral panic related to youth and technology (Critcher, 2008). Although sexting is not unlike earlier telephonic, written or face-to-face exchanges (Chalfen, 2009), these quick-fire exchanges that occur largely ‘under the radar’ have been greatly enabled, perhaps transformed, by the advent of convenient, affordable, accessible and mobile access to the internet (boyd, 2008). Also, the privacy and anonymity of much online communication would seem to proliferate the possibilities for youthful sexual communication (Subrahmanyam and Šmahel, 2011). Focus group discussions with teenagers suggest that sexting is primarily a form of electronically mediated flirtation (Lenhart, 2009). However, there have been revelations in some news stories of sexual activity among young people, made visible through the exchange of explicit, even possibly illegal images (if the images are of minors; Arcabascio, 2010; Sacco et al, 2010). Some argue that sexting is problematic only if the messages reach unintended recipients or are manipulated to produce hurtful effects, which is opening a new chapter in the history of sexual harassment (Barak, 2005; Ybarra et al, 2006). Concerns include, on the one hand, sexting as part of the much-claimed sexualisation of childhood (Greenfield, 2004) or the ‘hyper, (hetero)sexual commodification and objectification of girl's bodies’ (Ringrose, 2010, p 179) and, on the other, sexting as an activity that forms part of the abusive, usually adult-instigated, process of grooming (Davidson and Gottschalk, 2010). The boundary between what is fun and what is coercive may be difficult to distinguish, given the routine, often humorous exchange of sexual innuendo, rude jokes and swearing endemic in teenage conversation (National Campaign to Support Teen and Unplanned Pregnancy, 2008; Ringrose, 2010).
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".