STOR(Y)ING DESMADRE ON THE INTERNET: THE POLITICS, AFFECT AND ETHICSOF ONLINE QUEER LATIN AMERICAN CABARET ARCHIVES
Bibliographic record
Abstract
In this paper I discuss my doctoral research-creation project: the design of an online archive of the community materials of a Mexico City-based queer cabaret collective active between 2006-2012, called Burlesquimeras, which I was a member of. While digital photographs and social media certainly existed in the years Burlesquimeras was active, it was before the two were seamlessly integrated (at least in the Mexican context) through the ubiquity of smartphones and unlimited data. That is, an online search of Burlesquimeras does not yield a significant collection of photographs that can be potentially culled or scrapped from social media. Most of the digital photographs and other ephemera, have been stored by its members in the mess or clutter of the homes and hard drives of the community members. Moreover, I explain a concept I coined: “stor(y)ing”. It is influenced by theoretical structures and praxes that challenge and expand notions of evidence, sources and the possibilities of historic narratives, such as Hartman’s Critical Fabulation (2008, 2019), Cowan’s Cabaret Methods (Forthcoming) and Navarrete Linares’ use of Mesoamerican myth and cosmohistoria (2011, 2018). I propose that the very act of caring for these materials by their queer creators, albeit in a messy way, and precisely because it is in a messy way, is already an act of story-telling. I refer to this practice as stor(y)ing: a storage of materials that itself articulates a story.
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 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.032 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".