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Record W2900029557 · doi:10.7202/1053510ar

Toronto’s Cartographic Birth Certificate

2018· article· en· W2900029557 on OpenAlexvenueaboutno aff
Rick Laprairie

Bibliographic record

VenueOntario History · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsCartographyBirth certificateGeographyGenealogyHistoryDemographySociologyPopulation

Abstract

fetched live from OpenAlex

This article posits that the earliest map to have ever used the name Toronto as a place is uncovered. Previously unnoticed, the name “Tarontos Lac,” for today’s Lake Simcoe, is on a 1678 map by Jean-Baptiste-Louis Franquelin. His map, “Carte pour servir a l’eclaircissement du Papier Terrier de la Nouvelle France,” is now recognized as Toronto’s cartographic birth certificate. The article describes the map, discusses how the discovery came about and why the name may have gone unnoticed until now. This cartographic study is set in the history of the exploration of the Great Lakes region and the Mississippi River. Three other unsigned and undated period maps, often claimed as “Toronto” firsts, are also examined. These claims are dismissed, as revised attributions show them to have been by different cartographers and dated later than originally thought, making Franquelin’s map the oldest. The cartographic genealogy of the name Toronto is traced back through three and a half centuries to its initial appearance on Franquelin’s map.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0090.002
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0460.005

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.

Opus teacher head0.054
GPT teacher head0.233
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes2
Has abstractyes

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