Bibliographic record
Abstract
Young Lives has been a collaborative partnership between 12,000 study children, their families and their classmates, research institutes, universities and non-governmental organisations (NGOs) in four study countries, and a team based at the University of Oxford, together with researchers at University College London and other universities in the UK and USA.We are hugely grateful to the children and families who have participated in the study.Without their generosity, patience and willingness to talk to field workers regularly over a period of 15 years, often about sensitive subjects, the Young Lives study and its rich dataset would not exist.Special thanks are also owed to our collaborators, and to our research, communications and policy teams, data managers, field supervisors, and all other Young Lives staff for their contributions to so many aspects of the study, from the rigorous research design, high-quality data and publications, to the vital administrative support and robust engagement with policy and practice.Sharon Huttly merits special mention for her conscientious and steadfast stewardship of Young Lives during an earlier phase of the study, which created an essential foundation for the later research.This book has benefited from the contributions of many peoplealthough any errors are of our own making.In particular, we wish to thank Deborah Walnicki, who played an invaluable research assistance role by analysing qualitative data and sifting through interview transcripts for appropriate quotes, drafting selected texts, undertaking literature searches and compiling and checking references.Deborah displayed considerable flexibility, patience and good humour, despite the multiple demands placed on her.The book synthesises analyses produced by numerous study colleagues and reflects their careful and important work.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".