Bibliographic record
Abstract
In this article, we share results from a two-year ethnography of software writing to discuss some theoretical, methodological, and political limitations of contemporary approaches to networks and infrastructure. In examining how a novel technology comes into being over a reasonably broad period, one of us (Noon) observed how narrow conceptions of 'digital' computing impeded the initial development of alternative approaches to software writing for quantum computers (i.e. AQC). As a result, the subsequent production of quantum computing posed significant challenges to the methodologies that typically prevail in the study of networks and infrastructure. These undermined assumed divisions of hardware, software, and industrial practices, revealing a need to follow the course of key problems when accounting for the development of computing. By taking our cue from the insights and difficulties in this novel realm of computing, we speak back to the existing literature on networks and control by asking if the destabilization of our conception (and emblematic practices) of digital media might disclose alternative avenues for academic research, industry collaboration, and politics.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.047 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".