Relative pronominal tense : evidence from Gitksan, Japanese, and English
Bibliographic record
Abstract
This thesis investigates properties of tenses in English, Japanese, and Gitksan (Tsimshianic) with regards to the two major dimensions along which tense denotations can differ: 1) pronominal (Partee 1973; Enç 1987; Heim 1994) vs. existential (Ogihara 1989; von Stechow 2009) and 2) relative (Smith 1991; Ogihara 1989; Kusumoto 1999) vs. absolute (Comrie 1976; Dowty 1982). The past tense in English, the past and non-past tenses in Japanese, and the covert non-future tense in Gitksan will all receive relative pronominal denotations. An alternative analysis of Gitksan without a tense operator is also developed but eventually discarded in light of novel data before/after clauses. Taking this investigation of the three languages as a case study, this thesis also tackles a larger theoretical question: what is the empirical evidence for pronominal vs. existential and relative vs. absolute tenses? Teasing apart these two dimensions from each other as well as from the sequence of tense (SOT) issue, this thesis re-examines the existing empirical diagnostics of each tense property; are they sufficient conditions or merely necessary conditions? Are there alternative explanations for the empirical phenomena? To answer these questions, within each language, behaviours of the tenses are investigated across matrix clauses, attitude complements, relative clauses, and before/after clauses. From a cross-linguistic perspective, the three languages present both distinct puzzles and similarities with each other: English and Japanese are both overtly tensed and have been treated as canonical examples of SOT (Comrie 1985; Enç 1987) and non-SOT (Ogihara 1989; Kusumoto 1999) languages, respectively. English and Gitksan both have a dedicated future marker (Jóhannsdóttir and Matthewson 2007), and SOT constructions in English and non-future sentences in Gitksan exhibit similar temporal flexibility. Japanese and Gitksan both have a two-way distinction: Japanese has an overt past-non-past system, and Gitksan has a future-non-future system with a covert non-future tense; both languages rely on the Bennett and Partee (1987) effect to resolve temporal interpretations, as do SOT constructions in English. The results call for similar investigations across syntactic contexts to obtain a comprehensive picture of the temporal system in any given language.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".