Bitransitive Verbs, Ambitransitive Verbs
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
In English, there are verbs that take two objects, a direct and an indirect object: ‘I gave the waiter a tip’, ‘I cooked him dinner’. The direct object is the thing (seldom a person) that the verb directly acts upon. The indirect object is usually an animate being for or to whom the action is done. The indirect object can be expressed in two ways. Both the direct and indirect objects sometimes appear a simple nouns or pronouns, and in this case, the indirect object precedes the direct one (as in the examples given). The indirect object can also be indicated with the prepositions ‘for’ or ‘to’, in which case it follows the direct object: ‘I gave a tip to the waiter’ or ‘I cooked dinner for him’. In terms of Nahuatl grammar, we might term the indirect object the beneficiary (this term is to be understood broadly, as the indirect object may be harmed rather than benefited by the action). In these instances, the Nahuatl verb can take two objects, one representing the regular direct object and the other the beneficiary. Such verbs are called bitransitive. Unlike the case with English, where word order clearly distinguishes which is which when the beneficiary appears without the preposition, the bitransitive verbs in Nahuatl make no such formal distinction. In the natural order of things, the direct object will be inanimate and the beneficiary animate, but this is by no means always the case.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it