Evidence Type, Evidence Location, Evidence Strength
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
This paper investigates the question of whether ‘direct’ evidentials are amenable to an analysis as epistemic modals. Much recent literature advances modal analyses of evidentials, but direct evidentials pose prima facie problems for a modal analysis. In particular, typical epistemic modals differ from direct evidentials in that the former disallow direct witness, and convey reduced speaker certainty. In this paper I examine evidential elements in St’át’imcets (a.k.a. Lillooet; Salish), Gitksan (Tsimshianic), Nuu-chah-nulth (Wakashan), Cuzco and Wanka Quechua, English, Nivacle (Matacoan-Mataguayan), Cheyenne (Algonquian), Korean, and Tibetan. Based on the data presented, I propose that evidential contributions are more complex than is often assumed. Specifically, there are three different dimensions of meaning which evidentials may encode: (1) Evidence type (whether the evidence is visual, sensory, reported, etc.), (2) Evidence location (whether the speaker witnessed the event itself or merely some of its results), and (3) Evidence strength (the trustworthiness/reliability of the evidence). Each of the three dimensions has direct and indirect values, and particular evidential morphemes may be semantically complex, encoding information about one, two or all three of the dimensions. I then argue that contrary to what we might expect, evidentials which encode direct values on any of the three dimensions are compatible with modal semantics.
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.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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