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Record W2770126125 · doi:10.1353/llt.2017.0042

Who's on Secondary?: The Impact of Temporary Foreign Workers on Alberta Construction Employment Patterns

2017· article· en· W2770126125 on OpenAlexaffvenueabout
Jason Foster, Bob Barnetson

Bibliographic record

VenueLabour / Le Travail · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsAthabasca University
Fundersnot available
KeywordsGovernment (linguistics)ImmigrationConstruction industryIndigenousLabour economicsDemographic economicsLabour supplyBusinessPolitical scienceEconomic growthEconomicsEngineering

Abstract

fetched live from OpenAlex

The Canadian province of Alberta suffers from recurring labour shortages caused by its unstable resource economy. Alberta has historically relied upon interprovincial migrant workers to meet demand during “boom” periods. Between 2003 and 2013, the availability of interprovincial migrants was inadequate to meet overall demand for workers. Alberta’s construction industry and the provincial government sought to recruit workers from groups they defined as underrepresented, such as women and Indigenous peoples, to address this shortage. At the same time, the federal government altered its long-standing Temporary Foreign Worker Program (tfwp) to enable employers to hire an increasing number of international migrant workers. Alberta employers were among the most enthusiastic users of temporary foreign
\nworkers (tfws).5 The effect of tfws on how employers approach recruitment and retention of traditionally marginalized groups has not been extensively studied.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0020.003
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 head0.017
GPT teacher head0.291
Teacher spread0.273 · 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 designObservational
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

Citations14
Published2017
Admission routes3
Has abstractyes

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