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
After a quarter of a century of market reform, China has become the workshop of the world and the leading growth engine of the global economy. Its immense labour force accounts for some twenty-nine per cent of the world's total labour pool but all too little is known about Chinese labour beyond the image of workers toiling under appalling sweatshop conditions for extremely low wages. Working in China introduces the lived experiences of labour in a wide range of occupations and work settings. The chapters of this book cover professional employees such as engineers and lawyers, service workers such as bar hostesses, domestic maids and hotel workers, and industrial workers in a variety of factories. The mosaic of human faces, organizational dynamics and workers' voices presented in the book reflect the complexity of changes and challenges taking place in the Chinese workplace today. Based on extraordinary and thorough field research, this book will have a wide readership at undergraduate level and beyond, appealing to students and scholars from a myriad of disciplines including Chinese studies, labour studies, sociology and political economy.
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.425 | 0.582 |
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