Selfies or self-development? Humanitarians of Tinder (HoT) and online shaming as a moral community
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Humanitarians of Tinder (HoT) is a meme account found on Tumblr and Facebook that aggregates screen captures of Tinder profiles wherein users have posted photos of themselves participating in volunteer tourism activities throughout the Global South. For example, many users’ photos depict themselves embracing racialized children in their arms or participating in rituals or traditional ceremonies in cultures to which they do not belong. In this article, I argue that HoT establishes a moral community by shaming these individuals for presumably relying on these images to attract dates, while not recognizing their own complicity in colonial structures such as the volunteer tourism industry. Using strategies of humour to mock or deride these Tinder users for their actions as well as their appearances, HoT and its commentors engage in practices of digital vigilantism that seek to punish individuals for their behaviour, rather than the organizations and industries that structure these experiences. With this in mind, I demonstrate how Tinder users’ photos replicate images in recruitment media that are designed to advertise volunteer tourism expeditions. I further question how online shaming acts as a political action motivated by solidarity that comes to replace other actions, like volunteering.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it