Bibliographic record
Abstract
This thesis considers various theories of language typology put forward over the years, with particular reference to the more recent typologies of word order and the evidence they might provide of how and why languages change. Language typology and change is again arousing much interest in linguistic circles, but our understanding of it is still in the beginning stages and much work remains to be done on language classification. In Chapter II consider nineteenth and early twentieth century classificatory systems, which, for the most part, take the word as their fundamental unit. Tracing the development of typologies from the earlier purely morphological systems of von Schlegel and von Humboldt to the later morphological- conceptual system of Sapir, I compare and contrast the major classificatory systems of the period and indicate their limitations. In Chapter III review the syntactic typologies proposed recently by Lehmann and Vennemann. As a result of the upsurge of interest in syntax, both systems take the sentence as their fundamental unit and base their criteria on word order characteristics in consistent verb initial and verb final languages. I discuss the merits and inadequacies of both typologies and conclude that, as neither classificatory system appears to account for word order data satisfactorily, a further explanation must be sought. I suggest that perceptual strategies employed by speaker and listener can provide this explanation. In Chapter III I review some major work on perceptual strategies and find that misinterpretation of theoretically grammatical structures results from three causes: erroneous segmentation, discontinuity, and multiple centre embeddings. I then try to show how implementation of these perceptual strategies may account for or further explain the word order characteristics of Lehmann's and Vennemann's syntactic typologies. In Chapter IV I am concerned with how the syntactic typologies show evidence of diachronic word order change in language. I review several theories of word order change and comment on hypotheses regarding evidence of older word orders. I discuss the merits of each theory but try to point out where its claims can be questioned. I conclude that although many creditable observations and ideas have been presented within the framework of the syntactic typologies many of the connected hypotheses are subject to controversy and will have to be much more rigorously tested before their validity can be accepted.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".