Bibliographic record
Abstract
Governments, schools, and scholars worldwide have advocated for parental and community involvement in education to promote student achievement and strengthen democracy. One WERA International Research Network seeks to build on and expand traditional understandings of school-family-community partnerships by identifying various types of communities that engage in and advocate for educational change in ways and for purposes that are not always acknowledged in the existing literature. Two research reviews were undertaken, focusing on (1) parent and family empowerment and (2) educational policy advocacy by civil society actors. The common guideline was identifying and contextualising themes that asked how parents, families, and other civil society actors advocate for and engage with schools and educational policy reform. The first research review analysed more than 100 articles from 1996 to 2020, starting with anchor articles that studied parent empowerment in Canada and the UK. The second review period was selected to update research reviews focusing on interest groups and the politics of advocacy by Opfer et al. and Scott et al. The reviews showed how strategies and outcomes are currently influenced by advocates’ economic, political, historical, and national contexts. The COVID-19 pandemic closed schools worldwide and moved learning online for children who could access it. The disruption exacerbated threats to democracy and empowerment of local communities, especially for marginalised groups. Our findings showed that Indigenous partnerships with school boards, parent leadership training, and local community groups could help improve schools for all students and engage and enhance democracy through greater and more equitable parent and community involvement. Findings also warn that systemic policy networks (foundations, think tanks, businesses, academics, and government officials) may take advantage of crises to further privatise public education.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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; both teacher heads agree on what is shown here.
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".