Bibliographic record
Abstract
References to figures appear in italic type.References to footnotes show both the page number and the note number (12n2).A active inclusion 91 affirmative action 128, 131-133 Africa 21-22, 27, 33, 39, 44, 95, 98 see also sub-Saharan Africa; individual countries African-American children 47-48 agency 58-59 Akanksha 45 Asia 16, 21, 98 see also South Asia; individual countries aspirations 58-59 at-risk-of-poverty rate 12-13, 12n2 see also income poverty ATD Fourth World 48, 50, 55-56, 148-149 Atkinson, T. 15, 151, 156 austerity measures 126-127 Austria 84 B Bangladesh 55, 89, 96, 107, 142, 149 basic income for young adults 117-119 basic income security 88-99 Belgium 36, 119 birth, registration at 142 Bombay 45 boys 28, 93, 94 Brazil 3, 14, 92, 94, 99 bribery 21-22 bullying 51 CCanada 44, 50, 80n2 Caribbean 105 cash transfers 89-90, 92n5, 93-95, 97-99 castes 52-53 CESCR see Committee on Economic, Social and Cultural Rights (CESCR) child benefits 100 child deaths 13, 26 child deprivation 136-137, 136n2 child labour 37-38, 89, 93, 98 child mainstreaming 145 child marriage 55, 89 child poverty and aspirations 58-59 and bullying 51 and children's rights 143-145 comprehensive strategies for combatting 136-138 counting every child 142-143
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.866 | 0.791 |
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".