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Record W2899169262 · doi:10.3138/cpp.2017-070

Is There Evidence of an Information and Communication Technology Labour Shortage in the Canadian Labour Force Survey?

2018· article· en· W2899169262 on OpenAlexaffvenueabout
Alexander Thomson, Michael R. Veall, Arthur Sweetman

Bibliographic record

VenueCanadian Public Policy · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMicrodata (statistics)OvertimeInformation and Communications TechnologyEconomic shortageLabour economicsIncentiveContext (archaeology)ImmigrationWageDemographic economicsBusinessEconomicsPolitical scienceCensusSociologyLawMarket economy

Abstract

fetched live from OpenAlex

It has been suggested that there is a persistent and continuing shortage of information and communication technology (ICT) workers in Canada. We examine this claim in the context of confidential microdata from the Canadian Labour Force Survey for 1987–2016. For ICT- related occupations, there are indications of increases in hours per employee, overtime, and junior hiring from the mid-1990s to the early 2000s, but these tendencies do not persist beyond this period. There is some evidence that any tightness in the ICT labour market beyond the early 2000s may have been relieved by immigration rather than by wage increases, arguably dulling the incentives for Canadian residents of university and college age to train for and to pursue ICT careers.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.044
GPT teacher head0.272
Teacher spread0.228 · 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.

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

Citations6
Published2018
Admission routes3
Has abstractyes

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