Bibliographic record
Abstract
This intervention advances glitches as epistemological vectors for apprehending and engaging the significance of digitally-mediated spatialities that appear nonperformative against normative scripts of urban computational paradigms. Drawing on two strands of contemporary thinking about glitches as systemic design features of digital systems and as generative fissures within them, we mobilize a queer orientation that stays with the generative tensions of urban spatialities that present as idiosyncratic and as interrupting. We mobilize this epistemological approach through illustrative U.S. based examples of seemingly abandoned shared e-bikes, performatively ‘ugly’ homes, and wilful property dilapidation wrought through the registers of desire and aesthetics. In so doing, we show how glitch empistemologies render visible how the technocapitalist manufacturing of normative spatial desires for particular kinds of urban sociospatialities and aesthetic visual signatures are both secured and interrupted on digitally-mediated and -mediatized terrains. Glitch epistemologies establish the significance of small-scale disorientations in digital urban mediations, engaging these nonperformativities and non-computes as unexceptional openings onto everyday possibilities for politics in computational cities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.043 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".