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
We have two aims here. One is to provide an inventory and typological overview of the commonest pre-stem and suffixal tense-aspect markers across Bantu. We examine geographical distribution, phonological and tonal shape, and general semantic range. The other is to ask which of these might be assigned to Proto-Bantu, some 5000 years ago. We use a database of 100 languages, comprising 85 from all Guthrie's groups (A10, A20, etc) plus another 15 from his 15 zones. The most widespread pre-stem markers are: /a/, which comes in several tonal and vowel-length variations, representing 'past' in most languages and 'non-past' (possibly older focus (Nurse 2006)) in fewer languages; zero 'general present'; /ka/ 'itive, narrative, (far) past, (far) future'; /ki/ 'persistive, participial'; /laa/ 'future' and /la/ 'focus'. The first three certainly go back to Proto-Bantu, the status of the last three is less certain. The commonest suffixes are: /a/ 'neutral'; /e/ 'subjunctive'; /ile/ 'perfect, past'; /ag/ 'imperfective'; /i/ 'positive near past'; a vowel copy suffix 'positive near past'. The first five go back to Proto-Bantu, the sixth is innovation. We propose that /ile, i, the vowel copy suffix/ are connected. Finally, we mention four widespread but derived pre-stem markers.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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