Engaging with photographs: Conceptualizing socio-aesthetic agency and the cultural participation of young children in visual arts education
Bibliographic record
Abstract
Young children’s artistic activities have long fascinated researchers. Relatedly, research has produced two paradigms according to which a child is seen as either an independent, self-expressive artist or a developing maker/viewer of art. Both these modernist approaches are still recognizable in contemporary early childhood visual arts education, although recent research has shown such views to be problematic. The aim of this dissertation is to generate new information on children’s agency in terms of artistic activities and cultural participation. Thus, the theoretical frame of the research leans on relational agency, Pauline von Bonsdorff’s aesthetic agency, and Bruno Latour’s actor–network theory. The research focuses on preschoolers’ (N = 14) photography talk during a workshop organized in a Finnish early childhood education and care (ECEC) center. The data were produced via photo-elicitation interviews, where the children first discussed 13 contemporary art photographs and then took their own photographs inspired by the contemporary art photographs. The children’s self-authored photographs were discussed in small groups with the researcher and subsequently exhibited for a larger audience. In the analysis of the data, methods informed by discourse and conversation analysis were applied. Therefore, the children’s photography talk was approached functionally as an action that is, as a mode of agency. According to the results of this research, children’s agency is both a shared, interactional phenomenon and a socio-aesthetic event. It comprises playfulness and performativity, use of multimodal resources, and entanglement with materialities. Cultural participation is understood as a larger context for enacting the socio-aesthetic agency of children. It is defined as joining in a meaningful activity along with adults, belonging to a community as a respectful member, and being seen and heard in public discussions. Contemporary art is seen as a favorable venue for promoting children’s cultural participation and adults’ and children’s equal encounters. Visual arts education thereby provides a pedagogical site where both children and adults are co-players and searchers for meanings. Educators’ role in making explicit the connection between children’s artistic activities and wider contemporary visual culture is seen as significant.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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, 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".