Archaic methods, subculture sensibilities, outsider aesthetics & Instagram
Bibliographic record
Abstract
This project grew from an assignment to design a potential cultural artifact that could resist the forces of control (often called "taste", reeking of cultural capital and long-gone scholars with their legacies of gatekeeping) within visual culture. During the idea-generating process, I quickly realized how easy, enjoyable and interesting actually creating such an artifact would be - and that I had the means to. So. I created an Instagram account, both to host the artifact(s) and be the artifact itself; a space online to populate and fill with homemade collages reflecting myself, my life, my "tastes" and, most of all, what sorts of materials cross my desk throughout a day (show flyers, magazines, poems, crumpled paperbacks and family photos, doodles and drawings and all that and more). This paper was written alongside the creation, generation and sharing of the account and collages, meaning that analysis informed experiment shaped analysis, and so on and so forth. This written portion of the project describes my experiences with the various stages of enacting this cultural artifact. Accompanying images were taken during this process. Where it will go next, now created, realized and analyzed, is beyond the scope of this paper, but certainly worth observing.
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.
How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".