Bibliographic record
Abstract
The study of digital economies and the sociology of risk have, with few exceptions, a relationship of benign mutual neglect despite possible important connections between the two. This article aims to bridge the gap between these two fields using Beck’s theory of risk society to explore how the digital economy’s momentum of innovation is generating risks and limiting the scope of existing democratic decision-making via the power of the digital economy to create social faits accomplis outside of democratic control. Three specific risks emerging from the dynamics of innovation of digital economies are discussed as vignettes to illustrate these developments: (1) the remaking of interpersonal co-presence and solitary life; (2) the growing threats of AI to intensify unemployment and inequality; and (3) the impact on the environment of an ‘always on’ and ‘always upgrading’ digital communication ecosystem. With the gap between the potential and the actual use value of the digitalization of the infrastructure of life continuing to grow, this article argues that a different relationship between digital innovation and private and public spheres needs to be established to protect the effectiveness of contemporary democracy.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.035 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".