Verbs and Participants: Nonlinguists' Intuitions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Arguments and adjuncts play a crucial role in linguistic theories. Despite the vast body of research that assumes a distinction between arguments and adjuncts, not only in linguistics, but also in philosophy of language, psycholinguistics and neurolinguistics, there are no universally agreed-upon definitions distinguishing the two. The modest aim of this thesis is to investigate English speakers intuitions with respect to verbs and their arguments. To do so, the study makes use of the Core Participants Test, disguised in four different tasks, with each task eliciting, arguably, the same kind of intuitions. The results indicate that different tasks tap into either semantic or syntactic intuitions, or sometimes both. Overall, speakers' intuitions often matched linguists' views. to the members of my thesis committee, Ida Toivonen, John Logan, and Raj Singh. Ida Toivonen has taught and inspired me from the first time I heard her give a talk, despite the fact that at the time I understood only every other word. Through her knowledge, passion, patience and generosity she soon became my mentor and rolemodel. Ida taught me everything I know about arguments and adjuncts, syntactic theories, and ironically, along with Dana Isac, she taught me quite a bit about my native language. John Logan has taught me to think in an interdisciplinary fashion, and to translate my research questions and ideas across disciplines. Raj Singh's comments led to great improvements to the design of the study, and often made me aware of issues/alternative interpretations that I hadn't initially considered and which needed to be clarified. Each committee member had a great influence not only on this work, but also on shaping my Master's experience into a positive, productive, and enjoyable one.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it