Mechanization of Hearing in Chao Yuen Ren’s Dialect Research, 1927–1936: Senses, Objectivity, and Observation<xref xml:base="fn" rid="FN1"><sup>1</sup></xref>
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
When scientific research began in early twentieth-century China, a key issue was the acquisition of reliable empirical information through objective and precise observations. This article examines a specific case where a scientist grappled with such an issue: the linguist Chao Yuen Ren’s application of mechanical means in his phonetic studies. In the 1920s–1930s, Chao conducted a series of field and lab studies on the dialects in southern and central China. In contrast to traditional scholars’ exclusive reliance on sharp ears and rhyme books, Chao employed mechanical devices to inscribe and analyze the spectrographs of dialectical tones and used phonographs to record the articulations of his subjects. It is demonstrated that Chao’s machines not only provided a new method of observation; they also altered the theoretical understanding of certain fundamental categories in Chinese phonology, such as tones. Moreover, Chao did not aim to replace human perception with automatic mechanisms in empirical investigations. Rather, the use of machines in his research called for an active and engaged scientific persona.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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