Bibliographic record
Abstract
In the Reform Era there has been a dramatic increase in the number of peasant children left behind in ‘villages with an empty heart’, missing the middle generation of a family. These are the children of hundreds of millions of migrant workers, who have left rural China to work in more developed areas. Residence restrictions (hukou) prevent them from taking children with them. As many as 70 million are left behiind at the moment, in the care of grandmothers. These women, without whom China’s economic boom would have been impossible, care for their grandchildren for fifty weeks of the year. The parents send money home, and may eventually return, but in the meantime for the grandmother caring for several grandchildren is hard. Left-behind children do not have the educational advantages of urban children. Rural schools are poor; free education only goes up to junior middle school. Official pronouncements tend to be critical of grandparents for bringing up children ‘without culture’. The state is concerned that the children will grow up aware of their disadvantages, and may be difficult or even rebellious. In China’s history disadvantaged young men have turned into rebels; this includes many who joined the Communist Party.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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".