TypeForming: the Evolution of Typefaces
Bibliographic record
Abstract
An international panel of type and design experts gathered at Sheridan on September 21, 2015 to talk about the form of typography and how its history contributes to its future. The panelists were Matthew Carter, Rod McDonald, Allan Haley and Charles Nix of Monotype.\nThe discussion followed an exhibition and world premiere screening of a digitized and expanded film by Carl Dair, who designed Cartier – Canada's first Latin typeface.The film, Carl Dair at Enschedé: The Last Days of Metal Type features a digitized version of the 1957 silent film shot by Dair while studying in Holland with one of the last great European letter punch cutters, Paul Rädisch. It begins with a prologue by Canadian type designer Rod McDonald, who in 1998, updated and expanded Dair's Cartier typeface for digital technology. The film is narrated by Matthew Carter, one of the world's leading typeface designers who also studied with Rädisch. The film was co-produced by Sheridan College and Massey College at the University of Toronto.\nThe exhibit in the Sheridan Art Gallery, opened prior to the film screening, included artifacts such as didactic panels, photographs, sketches, tools, letters and books. It told the story of Carl Dair's quest to create Canada's first Latin typeface as part of the 1967 centennial as well as Rod McDonald's redesign.\nThe panel discussion was part of Sheridan’s Creative Campus Series.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".