“I Set the Camera on the Handle of My Dresser”: Re-Matter-Ializing Social Media Visual Methods through a Case Study of Selfies
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
This article is a confession about research trouble and the start of a narrative of research rectification. I begin this article with a review of new materialist theory and methods broadly and specifically those that contribute insight into interviews and photo elicitation such as <em>intra</em>-views and posthuman visual methods. I then detail the research methodology I used for an empirical study conducted last year to look at what young women experience while taking selfies, or images of their face and body to be shared on social media. After this fairly procedural account, I return to my messy research notes and video recordings, and—rather than reread—I re-trace and re-<em>matter</em>-ialize one specific interview with one young woman using new materialist methods (intra-views and reading images horizontally) to reveal data that would otherwise not have been evidenced via my original humanist methods. Re-<em>matter</em>-ializing describes my process as a researcher re-visiting not only the discursive moments, but the <em>affective encounters</em> and the <em>matter</em> of the research assemblage; meaning I move beyond the spoken data to look at how the material-discursive-afffective assemblage or arrangment of the interview room, technologies of data recording, props in the room, and embodied interactions of the participants were entangled in and vital agents in the production of data. In conclusion I detail the benefits of a posthuman re-tracing: 1) an attentiveness to the complex human and non-human agents in a research assemblage, 2) a <em>response-ability</em> or ethical duty of researchers to not reduce the complexity of the phenomena they study, 3) the importance of affect in the research encounter especially in visual methods, and, 4) a questioning of the implicit assumption that—of all steps in a research program—methodology is the least malleable.
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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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