“Die Maschine als Symbol ihrer Wirkungsweise”: Wittgenstein, Reuleaux and Kinematics
Bibliographic record
Abstract
In Philosophical Investigations 193–94, Wittgenstein draws a notorious analogy between the working of a machine and the application of a rule. According to the view of rule-following that Wittgenstein is criticizing, the future applications of a rule are completely determined by the rule itself, as the movements of the machine components are completely determined by the machine configuration. On what conception of the machine is such an analogy based? In this paper, I intend to show that Wittgenstein relied on quite a specific scientific tradition very active at the beginning of the twentieth century: the kinematic or the general science of machines. To explain the fundamental tenets of this line of research and its links with Wittgenstein, I focus on Franz Reuleaux (1829–1905), whose works were known to Wittgenstein. The first payoff of this investigation is to help distance the functionalist framework from which this passage is often read: Wittgenstein’s machines are not (or not primarily) computers. The second payoff is to explain why Wittgenstein talks about machines at this place in his discussion on rule-following: it is not the machine model in itself that is criticized in PI 193–94, but the “philosophical” temptation to generalize from it.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.034 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".