Bibliographic record
Abstract
In this article, taking inspiration from three volumes recently published on the topic, it is argued that in the digital space of neoliberal capitalism a new subjective condition is emerging which can be defined as "algorithmic subjectivity". As many authoritative commentators have already highlighted, one of the fundamental characteristics of neoliberalism is in fact its "constructivist" quality. In contrast to the naturalism of classical liberalism, this 'model' is characterized by political initiatives aimed at producing not only the action of rulers, but also the individual conduct of the governed in line with the needs of the market (Dardot & Laval, 2009) . In the neoliberal project it is therefore not a question of freeing the market from government functions, but rather of orienting these functions towards the active construction of the fundamental conditions for its functioning. In other words, as has been stated countless times, it is not a question of governing the market but of governing for the market. Producing a subjectivity compliant with the new means of digital quality production then becomes an unavoidable challenge for the new post-pandemic neoliberal capitalism.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.042 |
| Scholarly communication | 0.020 | 0.029 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".