Bibliographic record
Abstract
Serial verb constructions (SVCs), that is sequences of several consecutive verbs sharing certain features, form a well-established concept in descriptive and comparative syntax. However, there is no consensus concerning a systematic and universal definition of these constructions, leading authors like Bisang (2009) and Haspelmath (2016) to propose explicit criteria for their identification. Although Bantu languages are rarely described as containing SVCs, Tshiluba exhibits constructions that look suspiciously similar to them. This work therefore addresses two questions: (a) are these constructions SVCs in either Bisang’s (2009) or Haspelmath’s (2016) sense?; and (b) what are their key properties? Using various elicitation methods, I collected data indicating that these Tshiluba constructions conform to those definitions, and exhibit many properties which are usually associated with SVCs. Despite this evidence, further complications mean that these constructions remain ambiguous between serialization and asyndetic coordination, suggesting that we may be dealing with an on-going shift between the two (Andrason 2018), although further empirical confirmation is needed.
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 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 | 0.004 |
| 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) | 0.001 | 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 teacher head, 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".