Auto-Geneology: The Automobile and the Clode Family
Bibliographic record
Abstract
When asked how the automobile had impacted him, my father, Bruce, responded, “The car kept my teeth straight.”1 While growing up, a car meant that his parents could drive him to Toronto from Deep River every six weeks to visit the orthodontist. This was just one impact of the automobile. The introduction of the automobile to western society during the early 1900s had tremendous repercussions on North American society that would last through that century and into the next. This paper will chronicle some of the changes that the automobile brought to North American society. It will begin in the late 1920s and will be based on the experiences of my family. Through the eyes of one family, the Clode family, the larger changes that occurred to North American society as a result of the automobile can be seen. The paper will be based primarily on the experiences and recollections of my grandparents, Raymond and Marian White, and Frederick and Helen Clode, but will also draw on those of my parents, Bruce and Nancy Clode, and my aunt, Karen Clode. The information collected will largely be based on personal communications however; their experiences are quite representative of the larger social history of the automobile found in literature on the topic.2 Frederick (Fred) Clode and Helen Paul were born in Toronto in 1924. They met in high school and were married in 1948 in Toronto. Fred studied medicine at the University of Toronto and upon completion, he and Helen moved to the Yukon for two years where he practiced. They moved back to Toronto, where both Bruce and Karen were both born, and then to Deep River, Ontario.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".