Bibliographic record
Abstract
Tis book is one of the research outputs of an international and interdisciplinary workshop -held on 9-10 May 2019 in Vancouver -celebrating the work of Professor Emerita Susan B. Boyd, FRSC.During those two days, scholars from diferent backgrounds, disciplines, and jurisdictions engaged creatively and rigorously with themes that have animated Susan B. Boyd's scholarship during her career: the public/private divide, autonomy, ideology, privatization, empirical work, and family law reform.Tese themes are prevalent in our book and informed the contributors' engagements with the fundamental question that our book asks, namely, how do we overcome the gap between rapidly changing familial norms and norm-setting institutions that do not deliver just outcomes?Since we held that workshop and the presenters revised their papers for inclusion in this book, the world has changed in unprecedented ways, and the impacts of these transformations have yet to be measured.When we met, in person, on those gorgeous spring days in Vancouver, little did we know about what the near future held in store.None of us could have foreseen a global pandemic that would transform our lives, relationships, and families.Some of us were only too aware of the simmering racial tensions in the United States -and in Canada.But again, there was a sense of hope that the best was yet to come and that we were in a moment of positive change.Time has proven us wrong. 1 Te global COVID-19 pandemic has further entrenched many of the stubborn norms that our book highlights, and has underscored the need to unsettle certain norms along with the laws that sustain them.Te
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.356 | 0.190 |
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".