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Record W1569348588 · doi:10.3138/cjh.50.1.179

<i>The Italians Who Built Toronto</i>, by Stefano Agnoletto

2015· article· en· W1569348588 on OpenAlexaffvenueabout
Bruno Ramírez

Bibliographic record

VenueJournal of History · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceArtSociology

Abstract

fetched live from OpenAlex

The Italians Who Built Toronto, by Stefano Agnoletto. Bern, Peter Lang, 2014. xviii, 360 pp. $87.95 US (paper). As it has often happened in the history of industrial work in North America, it had to take a tragic workplace accident to expose and bring to public attention the shamefully sub-standard conditions to which workers were submitted by their employers and to set in motion a wave of labour militancy and government intervention that would bring order in the industry and effect significant reforms in industrial relations. The construction industry in post-World War II Toronto fits this pattern quite well. The tragic death, in March of 1960, of five Italian immigrants working on a water-main under the Don River brought to public light the unsafe and exploitative conditions that prevailed in that industry. More importantly, it triggered a series of organizing drives led by Italian labour activists. Their determination in the face of the employers' opposition drew into the action various trade-union bodies--from local to international ones--making it one of the major episodes in Toronto's postwar labour history. It also forced the government to enact safety standards and to make collective bargaining the mechanism ensuring the protection of workers' basic rights. These events and their many social and economic ramifications are at the heart of The Italians Who Built Toronto. Although they have been the subject of previous studies--most notably by Franca Iacovetta in her Such Hardworking People (Montreal & Kingston, 1992)--Stefano Agnoletto recounts this pivotal chapter in the immigration and labour history of Toronto in far greater detail drawing from a wide range of quantitative and qualitative sources and, in particular, from the many interviews he was able to conduct with workers and labour leaders who had participated in those events. He rightly places these developments in a larger context, one that saw the unprecedented construction boom occurring in Toronto during the 1950s and 1960s coincided with the largest influx of Italian immigrants to the city. With the majority of them originating from agrarian backgrounds, the construction industry provided the structural conditions for their proletarization. Moreover, in engaging this pivotal chapter in Toronto's post-World War II history, a good deal of the author's efforts are devoted to test a variety of perspectives that have been adopted in the study of issues such as ethnicity, class, gender, identity, and transnationalism. At the same time, by focussing on one specific sector of the industry--residential construction--Agnoletto is able to offer us an in-depth analysis of an urban universe peopled largely by Italian immigrants who, as workers and entrepreneurs, transformed that industry from an economic jungle (p. …

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: Review · Consensus signal: Review
Teacher disagreement score0.799
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0960.061

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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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
GenreReview

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".

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Citations0
Published2015
Admission routes3
Has abstractyes

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