Being the Only: An investigation into China's 'Selfish Generation' using text and photography
Bibliographic record
Abstract
This practice-based doctoral project uses a multi-modal, artistic approach—specifically, the combination of text and photography—to interpret the experiences of people whose lives were affected by China’s one-child policy (implemented in 1980, then revised in both 2016 and 2021). This research study focused on the impact of China’s Population and Family Planning Law (PFP Law) which is also known by the public as the ‘one-child policy’ (OCP) on the Chinese people. The study consisted of 50 participants (aged from 25 to 78 years old) who have experienced this law and are currently living in Mainland China, Canada, Australia, and the United States. The sample group included a mixture of only children, only child’s parents, and only child’s grandparents. The researcher investigated the most highly discussed topics that related to the policy whilst also contributing from their own lived experience as an only child. These topics include elderly care, willingness to give birth and have siblings, regret about only having one child, monthly income, true feelings on the policy, improvements on education rate, resources and son preference. In-depth interviews method discovered that elderly care is becoming the highest concern for the only child and their family. The main findings of the research study discovered that after the three-child policy was announced, most participants do not wish to have more than two children. Moreover, unlike the previous research’s findings, there are a significant amount of participants believe the only child is not selfish. The outcome of this doctoral research is an artist book named Being the only. Broadly qualitative and practice-based research methodologies combined with autoethnography have been applied to interview source material to create my own diaristic narratives combined with photography. In this instance, I used the combination of text and image as an artistic approach to documenting only child families' stories juxtaposed with documentary photographs of China today that show both state authority and daily life.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".