Clarifying the complexity: rethinking studies of variation in child care policy
Bibliographic record
Abstract
This thesis argues that existing accounts of variation in child care policy fail to systematically address, define, and measure the ways in which child care policy arrangements vary from jurisdiction to jurisdiction. Comparative studies of child care policy rely on broad or general descriptions of variation in child care policy that fail to provide a systematic comparative framework for understanding the extent, nature, and complexity of this variation. Drawing on comparative data measuring child care in the Canadian provinces, and a qualitative case study of child care policy in Alberta, I argue that child care policy arrangements display many inconsistencies and conflicting ideas that cannot be easily described and classified. This finding has important implications for the methods and theories used to describe and understand variation in child care policy.
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 | 0.104 | 0.201 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.016 | 0.019 |
| Science and technology studies | 0.012 | 0.116 |
| Scholarly communication | 0.023 | 0.044 |
| Open science | 0.008 | 0.023 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 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".