Key concepts in the work of Arnold Shepperson: representing communication and collaboration
Bibliographic record
Abstract
This article is divided into two main sections. The first section exposes the ways in which the work of Shepperson mobilises the concept of communication, while the second focuses on the concept of collaboration. First, we want to show how the work of Shepperson tackles the study of communication, by paradoxically adopting and rearticulating at the same time the theoretical linearity of the sender–receiver model, which was then the widely accepted canonical model for the study of communicative processes. Second, we will illustrate how the concept of collaboration appears in the works of Shepperson as both a cornerstone theme as well as a methodology orienting his critical discourses. In this second section, we approach Shepperson's critical discourses from a different critical purview by highlighting how exactly he deploys the theme of collaboration. With this emphasis, it becomes evident that collaboration is not only constitutive to the (re)production of knowledge in the world but, concurrently, becomes his representation of worldly experiences as well.
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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.046 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".