Building China’s Eldercare Market: The Imperatives of Capital Accumulation and Social Stability
Bibliographic record
Abstract
The paper investigates China’s effort to create an eldercare market to shed light on how China’s economic reform entailed the creation of new institutions (e.g., eldercare market including eldercare labour market) and the reconfiguration of existing institutions (e.g., governance and regulation, the family, and the community). All this was needed for the market to flourish while maintaining and strengthening the regime. An urban eldercare market, including an eldercare labour market, was created by local governments (i.e., municipalities, districts, counties, and towns) with central government policy directives, in order to address China’s demographic aging and care crisis. However, once enough demand and supply were created, local governments turned to New Public Management (NPM) to operate publicly funded eldercare institutions. The paper argues that NPM has different rationalities in China than in liberal democracies; in China, they strengthen the Party and contribute to the durability of the authoritarian rule, rather than “shrink the state”. However, in China as in the West, bureaucratic logic hampers the implementation of NPM and the governance of the eldercare sector. The implication of bureaucratic logic driving the regulation of the eldercare sector is that care is not at the centre of eldercare. The paper also argues that the commodification and privatization of eldercare, in line with the global trend, was a deliberate government policy aimed at creating a positive condition for the market economy to flourish, but at the expense of social reproduction/care. Unlike many Western transitions to market provision, this one entailed the decline in the extended family as the main eldercare institution of the immediate past. However, the commodification and privatization of social reproduction have been incomplete and met with resistance, prompting the state to invest more in the sector to maintain social stability. Data for this paper derive from personal interviews with key informants and eldercare workers, official document analysis, and secondary literature analysis from Chinese scholars in mainland China.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".