Bibliographic record
Abstract
The Amplify Engagement Report presents findings from the Children with Incarcerated Parents (CHIRP) study, which aims to estimate the number of children affected by parental incarceration across five Canadian provinces (British Columbia, Alberta, Saskatchewan, Ontario, and Nova Scotia) between 2015 and 2021. Recognizing the lack of national data and the profound impact of incarceration on child and family health, the study integrates insights from individuals with lived experience—including formerly incarcerated parents, caregivers, youth, and service providers—through focus groups held in February 2025. Key findings reveal that the number of affected children is alarmingly high, though likely underreported due to data limitations. Participants emphasized the need for qualitative context to complement the quantitative data, advocating for broader demographic representation, acknowledgment of systemic inequities, and inclusion of Indigenous perspectives. The report outlines three major outcomes desired from sharing this research: increased public awareness and education, enhanced support systems for families and children, and policy reforms that prioritize child-centered approaches within the justice system. The report underscores the importance of humanizing the data, addressing research limitations transparently, and amplifying the voices of those directly impacted to inform meaningful change.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".