Bibliographic record
Abstract
ABSTRACT Modernity held sacred the aspirational formula of the open future: a promise of human determination that doubles as an injunction to control. Today, the banner of this plannable future is borne by technology. Allegedly impersonal, neutral, and exempt from disillusionment with ideology, belief in technological change saturates the present horizon of historical futures. Yet I argue that this is exactly how today's technofutures enact a hegemony of closure and sameness. In particular, the growing emphasis on prediction as AI's skeleton key to all social problems constitutes what religious studies calls cosmograms: universalizing models that govern how facts and values relate to each other, providing a common and normative point of reference. In a predictive paradigm, social problems are made conceivable only as objects of calculative control—control that can never be fulfilled but that persists as an eternally deferred and recycled horizon. I show how this technofuture is maintained not so much by producing literally accurate predictions of future events but through ritualized demonstrations of predictive time.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".