Bibliographic record
Abstract
The Vanier Institute of the Family is pleased to present Families Count 2024. Drawing on the latest statistics and research, this publication informs readers about how families in Canada have changed (and not changed) over the past few decades. Families Count 2024 is organized into four main sections based on the components of the Vanier Institute’s Family Diversities and Wellbeing Framework: Family Structure, Family Work, Family Identity, and Family Wellbeing. This year marks the 30th anniversary of the United Nations International Year of the Family. Throughout the year, the Vanier Institute is working with the United Nations Department of Economic and Social Affairs (UNDESA) to recognize and articulate its global agenda to support family wellbeing in societies around the world. The Vanier Institute published the first edition of Families Count in 1994 to provide a foundation for the discussions and debates of that year. This year’s 30th anniversary provides an opportunity to re-engage in these important conversations, which we support with new information and research. The 2030 Agenda for Sustainable Development has also provided momentum and focus for Families Count 2024. In 2015, Canada joined 192 member states in adopting this framework for action at the United Nations General Assembly. Many of the Sustainable Development Goals (SDGs) at the heart of this agenda are closely intertwined with family wellbeing, addressing issues such as poverty, hunger, inequalities, and education. At the halfway point between Canada’s adoption of the framework and its end date of 2030, timely and accurate information on families can help inform actions that will drive progress toward the goals. Families Count 2024 presents data and findings in a way that is accessible to a wide range of audiences. The goals of this publication are to enhance the national understanding of families; to stimulate conversations among policymakers, educators, researchers, and journalists; and to strengthen the evidence base to facilitate the development of policies, programs, and services to enhance the wellbeing of all families in Canada. Norah Keating, Board Chair Margo Hilbrecht, Executive Director
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.309 | 0.175 |
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".