Understanding Effective Development: Using a Community–Academic Partnership to Create a Workshop and Interactive Toolkit for Parent Education
Bibliographic record
Abstract
A paucity of research exists on using action research with parents, particularly within the framework of parent education. The current study explores the development phase of a community-academic partnership (CAP) that designed a workshop and interactive toolkit to educate mothers on how to navigate social networking sites. The CAP (N = 10) was comprised of researchers, a community organization, and a group of mothers interested in the development of the parent education program. Participants completed an online survey wherein they endorsed and ranked the importance of facilitating and hindering factors present in the formation of the collaborative process, as well as provided formal feedback on the CAP. Although both collaborative processes (interpersonal and operational) were referenced as influential facilitating factors during the CAP’s development, operational processes were expressed as facilitators more often. Similar to other action research it appears that hindering factors are commonly not experienced during the development phase. In addition, it appears a quality action research project was conducted based on the successful fulfillment of partnership and participation, action, reflection, and significance. Overall, this study specifically makes a significant contribution to action research as it pertains to the development of parent 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 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 | 0.034 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".