Unmasking China’s Great Leap Forward and Great Famine (1958-1962) Through <i>Shunkouliu</i> (顺口溜)
Bibliographic record
Abstract
Satiric Shunkouliu (顺口溜), an oral folklore tradition among Chinese peasants known as “slippery jingles” or “doggerels,” express discontent and often contain disguised critiques of official propaganda. In this article, I call upon Shunkouliu to expose the reality behind the dogma during China’s Great Leap Forward and Great Famine (1958-1962). This departs from existing scholarship that has focused on written texts and interviews as primary data. Analyzing Shunkouliu demonstrates the collective efforts of Chinese peasants in speaking the truth. Through its satiric and disruptive qualities, Shunkouliu challenged official rhetoric by making erased realities visible and silenced voices audible. Recognizing Shunkouliu as legitimate data also challenges positivist criteria (representativeness and sample size) in assessing data credibility. I conclude this article by urging qualitative practitioners in the global South to explore forms of data beyond those traditionally examined within the parameters of qualitative research originating in the global North.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".