Beams of particles and papers: How digital preprint archives shape authorship and credit
Bibliographic record
Abstract
In high energy physics, scholarly papers circulate primarily through online preprint archives based on a centralized repository, arXiv, that physicists simply refer to as 'the archive'. The archive is not just a tool for preservation and memory but also a space of flows where written objects are detected and their authors made available for scrutiny. In this article, I analyze the reading and publishing practices of two subsets of high energy physicists: theorists and experimentalists. In order to be recognized as legitimate and productive members of their community, they need to abide by the temporalities and authorial practices structured by the archive. Theorists live in a state of accelerated time that shapes their reading and publishing practices around precise cycles. Experimentalists turn to tactics that allow them to circumvent the slowed-down time and invisibility they experience as members of large collaborations. As digital platforms for the exchange of scholarly articles emerge in other fields, high energy physics could help shed light on general transformations of contemporary scholarly communication systems.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchScholarly communication Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | MetaresearchScience and technology studiesScholarly communication Domain: Incentives · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | medium |
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 | 0.042 | 0.302 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.039 | 0.038 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.032 | 0.007 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".