Investigating romantic intimacy as experienced on mobile dating apps: a case study on fleeting online relationships
Bibliographic record
Abstract
This MRP explores the contemporary phenomenon of online dating in order to unearth the ways in which these dating experiences are being communicated and expressed online. By analyzing the communication of dissolved online romance as shared on YouTube, this MRP focuses on the concept of, and subsequent discourses surrounding fleeting intimacies in a modern, digital environment. Regarding the study, the author conducted a video content analysis of shared ‘Story Time’ videos on YouTube discussing the experience of being ghosted by a partner via a dating app. Through this research, the author found that the experience of fleeting romance is increasingly taking place in digital environments and expressed through oral storytelling practices. Furthermore, the particular gendered dynamics of the communication of fleeting intimacy are explored, with additional emphasis on the emotions felt and messages communicated with regard to the experience of ghosting. Using the sampled ‘Story Time’ videos as a case study, this MRP describes and analyzes the communication of modern fleeting romance in order to illustrate the increasing phenomenon of YouTube lifestyle vlogging as a form of connection, communication and sharing of intimate experiences in a digital environment.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".