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Record W2282982607 · doi:10.1017/s0963926815000607

Introduction: histories of Cold War cities

2015· article· en· W2282982607 on OpenAlexaffabout
Matthew Farish, David Monteyne

Bibliographic record

VenueUrban History · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsUniversity of CalgaryUniversity of Toronto
Fundersnot available
KeywordsRivalryCold warSummitDiplomacyContext (archaeology)Political scienceEconomic historyPoliticsIdentity (music)HistoryPolitical economyMedia studiesGeographySociologyLawArtCartographyEconomicsArchaeologyAesthetics

Abstract

fetched live from OpenAlex

The guest editors for this special issue of Urban History are both Canadian, and for many Canadians the hottest conflict of the Cold War might have been the 1972 ‘Summit Series’, eight hockey games played between the Russian Red Army team and an all-star cast of Canadian professionals. Without delving into the sporting glories of the series (Canada won it, four games to three, with one tie), we can aver that the event was as much about diplomacy, national identity and political-economic rivalry in the context of the Cold War as it was about skating and scoring.

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)0.000
metaresearch head score (Gemma)0.001
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: Editorial · Consensus signal: none
Teacher disagreement score0.154
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0080.005
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0490.005

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 head0.036
GPT teacher head0.242
Teacher spread0.206 · 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
GenreEditorial

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

Citations6
Published2015
Admission routes2
Has abstractyes

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