Bibliographic record
Abstract
This article offers a detailed textual reexamination of the ‘family resemblance’ passages to reconsider their implications for understanding art. The reassessment takes into account their broader context in the Philosophical Investigations, including the rule following considerations, and draws on a realist interpretive framework associated principally with the work of Cavell, Diamond, McDowell, and Putnam. Wittgensteinian “realism with a human face” helps us discern that the primary issue is not whether certain concepts are definable, posing a stark opposition between essentialism and its denial about kinds such as language or games. What is at issue is keeping uses of language in view in their variety and their broader life contexts. Focus on rules suggests more broadly that norms and values inhere in practices and play a constitutive role in determining the entities integral to those practices. From this perspective, a Wittgensteinian framework explains art as locally overlapping practices, each with their own constitutive norms and values for the works integral to them. What makes something art has normative force specific to a practice. This recognizes the historically contingent nature of art practices in a way that relational definitions or disjunctive ‘cluster’ explanations do not.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.064 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".