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Record W2475318605 · doi:10.1177/0306312716659373

Beams of particles and papers: How digital preprint archives shape authorship and credit

2016· preprint· en· W2475318605 on OpenAlex
Alessandro Delfanti

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocial Studies of Science · 2016
Typepreprint
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInvisibilityPreprintReading (process)TemporalitiesPublishingComputer scienceScrutinyOrder (exchange)Space (punctuation)Media studiesWorld Wide WebSociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

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.

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.

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 armCategoriesStudy designConfidence
gemmaMetaresearchScholarly communication
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptMetaresearchScience and technology studiesScholarly communication
Domain: Incentives · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.010
Scholarly communication0.0010.007
Open science0.0020.018
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.157
GPT teacher head0.384
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it