Dual Character Eliminativism
Clicks: 4
ID: 329888
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
0.9
/100
4 views
3 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #53 of 54 articles by views in journal of pharmaceutical analysis
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Abstract Extant dual character concept theories hold that utterances like `\textit{a} is not a scientist but, ultimately, \textit{a} is a true scientist' are felicitous because the head noun is polysemous, denoting a concept that permits dissociated categorization along descriptive and normative lines. This paper develops an eliminativist critique of such theories, arguing that this sort of dissociation is incoherent on a literal reading and requires pragmatic reinterpretation to achieve felicity at the level of speaker meaning. If such utterances are indeed coherent in context, they are more plausibly explained by context-sensitive category extension than by the hybrid lexical structures posited by dual character theories. Thus, eliminativism dispenses with dual character concepts and offers a semantically parsimonious treatment of double dissociation, {emphasizing} the importance of distinguishing between literal and loose categorization.
| Reference Key |
openalex_W7214431564
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Lucien Baumgartner |
| Journal | journal of pharmaceutical analysis |
| Year | 2026 |
| DOI |
10.1093/analys/anag075
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.