Polic(y)ing time and curriculum: how teachers critically negotiate restrictive policies
Bibliographic record
Abstract
Purpose The purpose of this paper is to theorize teacher agency as enacted through a P/policymaking lens in three elementary classrooms. Big-P Policies are formal, top-down school reform policies legislated, created, implemented and regulated by national, state and local governments. Yet, Big-P policies are not the only policies enacted in literacies classrooms. Rather, little-p policies or teachers’ local, personal and creative enactments of their values and expertise are also in play in daily classroom decisions. Little p-policies are teachers doing their best in response to their students and school contexts. Design/methodology/approach Adapting elements of discursive analysis, this interpretive inquiry is designed to examine textual artifacts, situated alongside classroom events and particular local practices, to explicate what teachers’ policymaking enactments regarding time and curriculum look like across three distinct contexts. Using three elementary classrooms as examples, this paper provides analytic snapshots illustrating teachers’ policymaking to solve problems of practice posed by state and school policies for curriculum, and for use of time at school. Findings The findings suggest that teachers ration (aliz)ed use of time in ways that enacted personal politics, to prioritize children’s personal growth and well-being alongside teachers’ values, even when use of time became “inefficient.” An artifact from three focal classrooms illustrates particular practices – scheduling, connecting and modeling – teachers leveraged to enact little p-policy. Teachers’ little p-policy enactment is teacher agency, used to disrupt temporal and curricular policies. Originality/value This framing is valuable because little-p policymaking works to disrupt and negotiate temporal and curricular mandates imposed on classrooms from the outside.
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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 | 0.023 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.050 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".