Recognizing Young People’s Civic Engagement Practices: Rethinking Literacy Ontologies through Co-Production
Bibliographic record
Abstract
In this article I argue that it is important to find a language to describe youth engagement practices in informal settings. I argue that many young people do not have the resources to be heard on visible platforms, but their work, and meaning making practices might provide important information about their ideas and relay key concepts about how communicational practices are constructed. Drawing on embedded, ethnographic and artistically informed projects with young people in communities, I argue for a deeper kind of listening. Artistic forms such as poetry, visual art, dance and music are important modes of engagement. I draw on cultural practice theory together with theory from new literacy studies and media studies to explore four questions:
 
 How do you craft what you know?
 How do you speak/make what you feel?
 How do you transform practice?
 How do you articulate action?
 
 I see these as components of the process of producing relationally oriented modes of address that others can also engage with. Taken together, they suggest a language of description for the mode that is civic engagement communicational practice, that is, oriented beyond individual experience but drawing from experience to make change happen in relational ways.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
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 | 0.001 | 0.003 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".