Visual and Performance-Based Research Feedback for Children and Youth: at the Crossroads of the Arts and the Social Sciences
Bibliographic record
Abstract
We are pleased to present our final issue of NEOS as Co-Editors.This diverse and fulsome issue features 15 contributions, composed of 3 invited commentaries and 12 articles, that explore and investigate communication in the worlds of children and youth.Through modes, methods, and approaches centering child-oriented communication-including creative expressions and multimodal methodologies-contributors invite readers into deeper understandings of how children and young people make sense of their world(s) and their place(s) within it.Following the work of Allison James (2007), whom several authors in this issue cite, the pieces collectively work towards seeing "childhood research [as] not simply about making children's own voices heard in this very literal sense by presenting children's perspectives.It is also about exploring the nature of the 'voice' with which children are attributed, how that voice both shapes and reflects the ways in which childhood is understood, and therefore the discourses within which children find themselves within any Society" (266).Thus, methods, voice, knowledge-creation, and questions about the nature of childhood and communication are central across this issue.To open this issue of NEOS, we offer three commentaries that speak to diverse ways of thinking with children and youth about how they engage in research and communicate about their lives.Julie Spray, author of The Children in Child Health: Negotiating Young Lives and Health in New Zealand (Rutgers, 2000), provides us with an illustrated representation of what it looks like to engage young research participants with visual methods.Spray's illustration reveals so many dimensions of youth-focused research including what it means to build rapport, to be supportive of young people's efforts amid fear of failure, to do research with (rather than on) young people, and to be reciprocal in our relations.Spray's work here and elsewhere illuminates the intersections of ethnography, visual representations, and the process of making art as a means of communicating with young people through research.Like Spray, Caitlin Nunn works at "troubling the borders of both 'researcher' and 'research'" by speaking to arts-based methods that are "affective, embodied, sensuous ways of knowing."Working with refugee young people, Nunn speaks to how art can illuminate important stories and histories, as well as generate research artifacts that can speak to many different audiences.Nunn reminds readers that pushing the boundaries of research processes and outcomes can be constitutive of a "hopeful practice" among young participants.
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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 | 0.018 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.016 | 0.012 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".