Constitutions of Nature by Teacher Practice and Discourse in Ontario Grade 9 and 10 Academic Science
Bibliographic record
Abstract
This thesis presents an ethnographic study, based broadly on principles and methods of institutional ethnography, on the constitution of nature by nine Ontario Grade 9 and 10 Academic Science teachers. The intent of this methodological approach is to examine how the daily practice of participants works toward constituting nature in specific ways that are coordinated by the institution (Ontario public school and/or school science). Critical Discourse Analysis and general inductive analysis were performed on interview transcripts, texts related to teaching science selected by participants, and policy documents (i.e. curriculum; assessment policy) that coordinate science teacher practice. Findings indicate specific, dominant, and relatively uniform ontological and epistemological constitutions of nature. Nature was frequently constituted as a remote object, distant from and different than students studying it. More complex representations included constituting nature as a model, machine, or mathematical algorithm. Epistemological constitutions of nature were enacted through practices that engaged students in manipulating nature; controlling nature, and dominating nature. Relatively few practices that allow students to construct different constitutions of nature than those prioritized by the institution were observed. Dominant constitutions generally assume nature is simply the material to study, from which scientific knowledge can be obtained, with little ethical or moral consideration about nature itself, or how these constitutions produce discourse and relationships that may be detrimental to nature. Dominant constitutions of nature represent a type of objective knowledge that is prioritized, and made accessible to students, through science activities that attain a position of privilege in local science teacher cultures. The activities that allow students to attain the requisite knowledge of nature are collected, collated, and shared among existing science teachers. Activities are adapted to meet the knowledge requirements of the curriculum, which is institutionally coordinated by a system of management, based on accountability and performance. Thus, teachers come to see teaching practice that â worksâ as contained in those science activities that engage students in learning nature as a specific representation (model/machine) or through science methods that control students learning so that they arrive at the correct knowledge. This allows teachers to assess and evaluate studentsâ acquisition of the institutionally valued knowledge of nature. This system of coordination is sustained through discourse that enables teaching practices that aligns with institutional priorities of measuring performance, while at the same time, limiting teachers from being able to conceive of other teaching practices that might enable different constitutions of nature.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".