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Record W4404410757 · doi:10.2307/jj.21931889

Northern Ontario in Historical Statistics, 1871–2021

2024· book· en· W4404410757 on OpenAlexaboutno aff
David Leadbeater, Pat Marcuccio, Charlene Faiella, Tomasz Mrozewski, Caitlin Richer

Bibliographic record

VenueLes Presses de l’Université d’Ottawa | University of Ottawa Press eBooks · 2024
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyStatisticsHistoryMathematics

Abstract

fetched live from OpenAlex

Based on original historical tables, Northern Ontario in Historical Statistics, 1871–2021 offers an overview of major long-term population, social composition, employment, and urban concentration trends over 150 years in the region now called “Northern Ontario” (or “Nord de l’Ontario”). David Leadbeater and his collaborators compare Northern Ontario relative to Southern Ontario, as well as detail changes at the district and local levels. They also examine the employment population rate, unemployment, economic dependency, and income distribution, particularly over recent decades of decline since the 1970s. Although deeply experienced by Indigenous peoples, the settler-colonial structure of Northern Ontario’s development plays little explicit analytical role in official government discussions and policy. Northern Ontario in Historical Statistics, 1871–2021, therefore, aims to provide context for the long-standing hinterland colonial question: How do ownership, control, and use of the land and its resources benefit the people who live there? Leadbeater and his collaborators pay special attention to foundational conditions in Northern Ontario’s hinterland-colonial development including Indigenous relative to settler populations, treaty and reserve areas, and provincially controlled “unorganized territories.” Colonial biases in Canadian censuses are discussed critically as a contribution towards decolonizing changes in official statistics.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.186
Teacher spread0.173 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueLes Presses de l’Université d’Ottawa | University of Ottawa Press eBooksSame topicCanadian Identity and HistoryFrench-language works237,207