Editorial: A Reflection on the Role of New Media — From Peer-to-Peer to Protest
Bibliographic record
Abstract
What does the concept of ‘new’ mean in relation to the technologies that encompass new media? Similar to the path of preceding technologies, new media has permeated many different social, political, and economic realms, transforming the way we carry out daily life. However, the emergence of new media has given rise to a set of assumptions surrounding technological advancement that overlook historical dimensions and ways of thinking about new technology. More specifically, the ‘newness’ of new media carries with it a renewed sense of optimism about technology and its ability to drive social change, revive political landscapes, and foster economic prosperity. One of the aims of this volume is to enlarge this dialogue by further illustrating the depth and scope of issues surrounding new media and the contexts in which new media technologies function.
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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 | 0.013 | 0.057 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.027 | 0.033 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".