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Record W2158278890 · doi:10.1017/s0008423907070540

Marginal Man: The Dark Vision of Harold Innis

2007· article· en· W2158278890 on OpenAlexaffabout
Geoff Martin

Bibliographic record

VenueCanadian Journal of Political Science · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsMount Allison University
Fundersnot available
KeywordsWatsonWork (physics)PoliticsManagementArt historyMedia studiesSociologyHistoryPolitical scienceLawEngineeringComputer science

Abstract

fetched live from OpenAlex

Marginal Man: The Dark Vision of Harold Innis, Alexander John Watson, Toronto: University of Toronto Press, 2006, cloth, $65.00, pp. xi, 525. In the study of Canadian political thought, a young doctoral student wrote, and defended in 1981, an excellent PhD dissertation on Harold Innis. Unlike many works, it was based as much on an exhaustive examination of Harold Innis' papers as it was on Innis' published works. Unfortunately, A. John Watson did not continue in academia and his work was ultimately accessible only to the committed Innis specialist, willing to visit the U of T's Robarts Library or consult microfilm. After half a career as CEO of Care Canada, the international relief organization, Alexander John Watson has revised and published this work, making it accessible to a much broader audience.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score0.657

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0310.047
Scholarly communication0.0100.008
Open science0.0010.006
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.012
GPT teacher head0.284
Teacher spread0.272 · 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 designQualitative
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

Citations0
Published2007
Admission routes2
Has abstractyes

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