Diachrony and Diachronica
Bibliographic record
Abstract
The year 2023 marks volume 40 of Diachronica.To mark the occasion, 40 linguists working on different aspects of language change have contributed to "40@40"providing brief vignettes about the history of the field, current questions, where current debates are strongest, and where we're headed.These contributions will be published across the next few issues of the journal.In this first set of reflections, five authors discuss a range of big picture questions about our field.Reading these contributions has also led me to think about the field I entered as an undergraduate student in the last few years of the 20th century.The most exciting development in my view is the breaking down of what Paul Kiparsky (2006) has called "Saussure's Firewall": the strict separation of synchrony and diachrony.As Aronoff (2017) has discussed, Saussure's notion of language change owes a great deal to the (then) recent invention of cinema: a thousand sequential photographs all lined up, which when run together give the appearance of motion from a set of static images.So too diachrony: thousands of minimally distinct synchronic grammars, when lined up, give the appearance of change over time.Such a metaphor -and its entailments -has been a useful construct for the study of language, with many aspects of language relying on it, whether implicitly or explicitly.Such a view also siloes variation from change: variation is synchronic, but "change" only happens once variation itself varies across time.Another line of argument is that language is in the brain: to understand language, we need to understand the mind.Minds have no access to past histories of their languages, so the argument goes, so all that is needed is knowledge of the internal mental grammar.As Joseph and Janda (1998: 194) put it: Diachrony is best viewed as the set of transitions between successive synchronic states, so that language change is necessarily something that always takes place in the present and is therefore governed in every instance by constraints on synchronic grammars.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".