Getting Down to Brass & Wax: The Material Culture of Physics at Canadian Universities, 1890-1939
Bibliographic record
Abstract
This thesis explores the scientific apparatus of physics at Canadian universities from 1890 to the onset of World War Two. It is divided into two complementary sections. The first section adopts a collections and material culture approach to analyze the accumulations of historical apparatus that emerged at departments of physics. Through considering how artifacts in these environments avoid destruction, how they come to form collections, and the implications of these processes for the surviving artifacts as evidence of the scientific past, it complicates existing accounts of these narratives. It examines the close and definitive relationship these collections have to their home department and how they are shaped over time, most notably by technical members of staff. This dissertation concludes that collected sets of surviving artifacts at university departments form a particularly rich historical source due to their shared history, while simultaneously noting the importance of fully considering these collections’ formations and evolution through to the present day. The second section of the dissertation offers a materially-focused history of experimental and practical physics as it emerged and matured in Canada. Informed directly by the material remnants of each university’s physics programme and the discussion in the first section, it traces shifts in thinking about teaching and research in physics relevant to both Canadian and international contexts. This includes the use of imported instruments to establish legitimacy away from scientific centres, the early influence of engineering and technical programmes, the rapid developments in research and teaching in the period following the First World War, and the central importance of department workshops, technical skills, and makers throughout this period. Together, these themes contribute a history of physics in Canada in which materiality, in the form of equipment and laboratory spaces, played a definitive role. This dissertation demonstrates the ability of large sets of seemingly mundane scientific artifacts to contribute a useful narrative history, and reveal new details about less-well recorded elements of the history of science, such as the role of technical staff. As such, it represents a model for future work examining the large quantity of historic scientific material at university departments.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.057 | 0.031 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".