Sheri Madigan and the Determinants of Child Development Lab, Calgary
Bibliographic record
Abstract
Abstract In Chapter 5, I explore the work of Sheri Madigan, one of the ‘third generation’ of developmental scientists working on attachment and caregiving. Her work illustrates the contemporary opportunities and challenges facing this generation of researchers. From Van IJzendoorn and Bakermans-Kranenburg, one set of early mentors, she has absorbed a passion for meta-analytic research. The chapter explores the meta-analyses undertaken by Madigan and colleagues, which draw together the current state of knowledge of child attachment and caregiver sensitivity. This has included surprising findings that have challenged long-standing assumptions within attachment research. Another of Madigan’s mentors has been Lyons-Ruth, with whom she shares a clinical orientation towards the study of attachment and caregiving. The chapter also addresses work by Madigan and collaborators to adapt the AMBIANCE measure, developed in Lyons-Ruth’s lab, for use by professionals in applied practice with families. Finally, the chapter addresses a new international project led by Madigan, the CARE Collaboration, that seeks to draw together researchers and practitioners interested in attachment.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".