Bibliographic record
Abstract
Jerry Fodor and Ernie Lepore have argued that inferential roles are not compositional.It is unclear, however, whether the theories at which they aim their objection are obliged to meet the strong compositionality requirement they have in mind.But even if that requirement is accepted, the data they adduce can in fact be derived from an inferential-role theory that meets it.I explain this in terms of Robert Brandom's substitutional conception of inferential roles.The several objections the proposal invites are worth discussing because they rest, I think, on neglect of some interesting and important facts about inferential roles.Whether Fodor's and Lepore's strong compositionality requirement is justified or not, then, inferential-role theories do not have the problem that they claim to have identified.Jerry Fodor and Ernie Lepore have argued -"frequently, loudly, and in many places" 1that inferential roles are not compositional.If they are right then things look grim for any semantic theory that incorporates a notion of inferential role.One problem with their argument is that it is unclear whether the theories at which they aim their objection are obliged to meet the strong compositionality requirement they have in mind.But even if that requirement is accepted, the data they adduce can in fact be derived from an inferential-role theory thats meets it.I explain this in terms of Robert Brandom's (1994) substitutional conception of inferential roles.The several objections the proposal invites are worth discussing because they rest, I think, on neglect of some interesting and important facts about inferential roles.Whether Fodor's and Lepore's strong compositionality requirement is justified or not, then, inferential-role theories do not have the problem that they claim to have identified. The objectionFodor and Lepore support their objection on examples such as the following.Suppose... that you happen to think that brown cows are dangerous; then it's part of the inferential role of "brown cow" for you that it does (or can) figure in inferences of the form "brown cow → dangerous."But, at first blush anyhow, this fact about the inferential role of "brown cow" doesn't seem to derive from facts about the inferential roles of its constituents in the way that, for example, the validity of inferences like "brown cow → brown animal" or "brown cow → not green cow"
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.014 | 0.050 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".