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Record W2215064346 · doi:10.1515/9780773589391-006

Infrastructures of Census Taking

2014· book-chapter· en· W2215064346 on OpenAlexaboutno aff
Evelyn Ruppert

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2014
Typebook-chapter
Languageen
FieldMathematics
TopicCensus and Population Estimation
Canadian institutionsnot available
Fundersnot available
KeywordsCensusGeographySociologyDemographyPopulation

Abstract

fetched live from OpenAlex

On 2 June 1911, Thomas Vance, census commissioner for Centre Toronto, expressed delight with the way things had gone so far with the enumeration of his district.Based on his experience overseeing the same district in the 1901 census, things were proceeding ever more efficiently.Vance had accompanied three different enumerators the previous evening during their rounds of "The Ward" to ensure that counting the "foreign population" was going smoothly.And, leading up to census day, he had participated in meetings with the Ontario Special Commissioner Mr J.C. Macpherson and with the other four commissioners responsible for Toronto.He had also overseen the hiring of enumerators and their training based on instructions issued by Archibald Blue, the chief census commissioner for the Dominion of Canada.Vance was part of a vast operation that included many actors beyond census officials.There were, of course, the politicians.At the top of the list was Minister of Agriculture Sydney Fisher, who was responsible for the "counting

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.255
Teacher spread0.219 · 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 designTheoretical or conceptual
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

Citations0
Published2014
Admission routes1
Has abstractyes

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