Bibliographic record
Abstract
Unlike the memes of popular digital culture, philosophical understanding accumulates through the patience of reflection on the long-term implications of human action. The paper will draw upon the recent work of Paul Virilio to explain the threat that the speeds of digital culture pose to philosophy, both as an institutionalised discipline of human inquiry with a just claim to public support, and as an intellectual practice with a just claim to public relevance. If Virilio is correct, the trajectory of technological development is towards the displacement of human decision making from all spheres of social life (political, economic, military, cultural, and technical-scientific) because human thought is too slow. Hence, there are moves towards eliminating the deliberative function of human thought in favour of pre-programmed algorithms that can trade a stock or fire a missile in immediate response to a pre-determined set of objective circumstances. Philosophy cannot keep pace. Since it is committed to an open-ended dialectic of interpretation, reason giving, critique, and rejoinder, its time frames are incompatible with immediate response, and would, if allowed to operate in politics or economics, impede the ‘efficient’ execution of routines. However, the ‘efficient’ execution of the dominant political and economic routines is undermining the conditions of life on the planet. Hence, the defence of slow philosophical thinking is at the same time the affirmation of a different temporality of life, politics, economics, and cultural interaction. Philosophy is not a luxury that humanity can no longer afford, but the vital necessity of historically informed intelligence the solution of our most pressing environmental and social problems requires more than ever.
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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.053 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.010 |
| 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".