Bibliographic record
Abstract
“If I'd seen the machete, I'd have handled it differently.” (Headline, Vancouver Sun , June 6, 2001) The polysemy of past-tense forms As noted at the end of the last chapter, distanced future-reference conditionals use past-tense forms rather than future ones. Out of context, (1) could be an assessment of future eventualities, viewed with negative epistemic stance: (1) If he decided to file the suit, the hospital's lawyers would be allowed to interview him for discovery. However, (1) could equally well be a past narrative description of a conditional situation – a situation which was neutral in stance and future relative to the characters' situation.), only context tells us whether the past-tense verb forms are marking tense or epistemic stance. Fleischman (1989) has discussed the pervasive crosslinguistic correlation between past-tense marking and distanced stance. It has also been noted that tense marking is one of the most basic cues for relationships between mental spaces (Fauconnier 1985 [1994], 1997; Cutrer 1994; Mejías-Bikandi 1996). In Example (2) there is no ambiguity. The conditional presented is in past-tense form not because it is distanced epistemically, but because it is embedded in a past-tense narrative space. (2) The gun had dug a deep bruise into my side when I tumbled from the boxcar. I'd be sore for four or five days, but if I was careful I'd be okay … Lotty dispensed that verdict at her clinic Sunday afternoon … (SP. HT.233)
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 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 | 0.002 |
| 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 | 0.007 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".