Rhetorical casuistry and institutional contradictions: China's transformation from plan to market
Bibliographic record
Abstract
This paper discusses how Chinese communist leaders use casuistry to stretch the concept of communism to open up space for arguments justifying free-market practices. Through the use of casuistry, Chinese leaders created slogans and theories that were strategically ambiguous and multifaceted. New and controversial meanings were introduced gradually and subtly, and the preservation of old and orthodox meanings ensured some degree of continuity with the past. Diverse audiences may have highlighted different aspects of these slogans and theories, interpreted them differently, and employed them selectively to support their own propositions. Casuistry enables the formation of new markets and practices and the radical transformation of institutionalized beliefs under the disguise of gradualism and incrementalism. It can be used to justify actions and policies ranging from the political left to the right, because a wide range of policies and actions can find support in the re-interpreted original slogans and theories. Therefore, casuistry effectively creates the space for new arguments and practices within the context of entrenched interests and ossified belief structures.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".