Assembling kindergarteners’ agency during classroom free play time
Bibliographic record
Abstract
Countless studies have documented that free play is an ideal space for children to exercise agency and become independent individuals. However, the narrative of free play within Canadian schools remains problematic. Drawing from relational lenses (Oswell, 2013), we adopted the construct of entanglement (Deleuze & Guattari, 1987) to explore how children's agency manifested during kindergarten free play time. A qualitative research design utilizing action research methodology (Stringer, 2014) was used to invite kindergarten teachers and education stakeholders to participate in the study. Participants came together in eight focus groups where the teacher-researchers shared evidence about how play happened in their classrooms. Thematic analysis (Babbie, 2010) revealed that kindergarteners' agency was entangled in free play scenarios where children felt safe; further, daily encounters with free play time became a significant assembled piece for children's agency capacity to unfold. The study also indicated that teachers' perceptions, the allocation of time, and the design of classroom spaces permitted children to enact their expressions of agency. The study suggests that renegotiating the discourse of free play as a relational space for kindergarteners' agency capacity to be practiced could shift the ways free play is defined within Canadian kindergarten classrooms and school policies.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".