Space in tense: The interaction of tense, aspect, evidentiality, and speech act in Korean
Bibliographic record
Abstract
This dissertation investigates the interaction of tense, aspect, evidentiality, and speech acts, using Korean as a test case. I propose that Korean has two types of deictic (indexical) tense-simple deictic tense and spatial deictic tense. This makes possible a systematic account of the temporal interpretation of tenses, aspects, and moods that also incorporates evidentiality. By showing that the Korean evidential system should be analyzed as part of the tense-aspect system, this study contributes to current research on the formal analysis of inflectional systems in the world's languages. First, I give an analysis of the simple suffix -ess and the double form -essess. The distinction between these two parallels the distinction between the perfect and the past manifested in most Indo-European languages. The simple form -ess is a perfect and the double -essess is a deictic past tense. Next, I treat the suffix -te and argue that not only temporality but also the notion of space is relevant to its analysis: it is a spatial deictic past tense denoting a certain past time when the speaker perceived either a given event itself or some evidence of the event. Thus, -te directly relates to evidentiality. In addition, -te has a present tense counterpart, the spatial deictic present form -ney. My analysis results in the claim that some suffixes are ambiguous between aspects or moods and evidentials. For example, if the suffix -ess occurs with a simple deictic tense, it functions as a perfect. But if it occurs with a spatial deictic tense, it functions as an indirect evidential. In sum, a definitive analysis of Korean tense, aspect, and mood morphology incorporates two distinctions that operate in tandem: one distinction is simple deictic tense and aspect and the other distinction is spatial deictic tense and evidentiality. The basic difference between evidential sentences and non-evidential sentences is captured in terms of speech acts: unlike non-evidential (declarative) sentences, evidential sentences do not make assertive claims. Even direct evidential sentences in Korean do not express the speaker's commitment to the truth of the proposition described.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".