Bibliographic record
Abstract
I address two claims that Miščević makes in his book Thought Experiments. The first claim is that literary fictions belong to the broader category of what he terms “Imaginative Enactments in Thought” (IET’s), but are not TE’s properly understood. The second claim is that TE’s are indispensable to analytic philosophy. Both claims appeal to Miščević’s discussion in the opening chapter of what it is for something to be a TE. I argue for the following conclusions: (1) If TE’s are defined in the way that Miščević proposes, then there can in fact be (and indeed are!) works of literary fiction that qualify as TE’s. (2) If TE’s are defi ned in this way and are explained in terms of mental models, then whether there can in fact be analytic philosophy without TE’s depends upon how we understand the relationship between TE’s and counter-factual thinking more broadly construed.
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 | 0.038 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.057 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 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".