Canada at 150: Critical Historical Geographies
Bibliographic record
Abstract
At the 2017 Canadian Association of Geographers (CAG) annual meeting in Toronto, the CAG’s Historical Geography Speciality Group sponsored a set of four panel sessions titled Canada at 150: Critical Historical Geographies . Originally conceived as a workshop that would precede or follow the conference, the sessions were eventually folded into the meeting, which permitted an assortment of conference-goers to attend. As the title suggests, the 150 th anniversary of the Canadian state provided an occasion to reflect on Canada as a collection of persistent, unfinished and, in many cases, unjust geographies—in contrast to the effervescent celebrations occurring elsewhere. The organizers encouraged participants to link their own projects and preoccupations to the various geographies associated with the sesquicentennial. The following represents nearly all of the conference presentations, converted into publishable format and lightly edited by organizers hesitant to meddle. Together, they stand as a collective if hardly exhaustive expression of confidence – in the role of historical geography for the critical consideration of Canada, and in historical geography tout court .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.033 | 0.027 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.017 | 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".