Bibliographic record
Abstract
This thesis deals with direct object nouns case-marked differentially. According to the commonly assumed generalization nouns marked with ACC case are prototypical objects representing high transitivity, whereas nouns marked with non-accusative cases are not. However, such a view ignores the possibility of a much finer distinction and fails to account for empirical data from languages with rich case morphology, such as Ukrainian. Given the complexity of the phenomenon under study the main objective of our investigation is to account exhaustively for all possible instances of non-accusative case marking and case alternations on direct objects in Ukrainian trying to classify and analyze the data by specifying the factors that condition the distinction ‘accusative versus non-accusative case marking’ and by integrating the phenomenon of differential object marking (DOM) into a formal model. We present DOM as a phenomenon that, together with the phenomenon of unaccusativity, can be subsumed under a broader concept of non-accusativity (defined as inability of verbs to assign ACC case). In this context we show that in Ukrainian and French morphosyntactic case realization has semantic underpinnings and that issues related to case valuation emanate from the intersection of different phenomena – DOM and nominal incorporation, DOM and verb typology, DOM and the process of (de)transitivization, and so on. However, the (morphosyntactic) visibility of those points of intersection varies from one language to another. Generativist distinction between syntactic (abstract) and morphological cases as well as the functionalist idea that case markings can be characterized as morphemes having different functional applications constitute the basis of our analysis of data. Using the typological views of these two approaches on the category of case as guidelines in our classification of collected data, we resort to minimalist formalism. Case is treated as an uninterpretable feature and a clear distinction is drawn between two types of case valuation – case checking and case assignment. Structural cases are checked during verb-raising and inherent (lexical) cases (among which we find predicate and default cases) are assigned either by a weak (or defective) v or by (an overt or null) preposition (P) in situ.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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 teacher head, 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".