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Record W1522802466

Skill Shortages and Advanced Technology Adoption

2001· preprint· en· W1522802466 on OpenAlexaffabout
David Sabourin

Bibliographic record

VenueRePEc: Research Papers in Economics · 2001
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsEconomic shortageBusinessMarketingLabour economicsEconomic growthEconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the extent to which establishments in the Canadian manufacturing sector experience occupational skill shortages, and to the extent that they do, whether these shortages appear to act as impediments to advanced technology adoption. Plants adopting advanced technology report shortages, particularly when it comes to professionals, such as scientists and engineers, and to technical specialists. Whether these shortages pose labour-market problems depends very much on the solutions adapted by the establishments experiencing the shortages. This paper finds that labour shortages did not appear to block technology adoption since those establishments that reported shortages were also the most technologically advanced. Although they faced a greater need for skilled labour, they were able to solve their shortages.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.034
GPT teacher head0.295
Teacher spread0.261 · 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.

Study designTheoretical or conceptual
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

Citations13
Published2001
Admission routes2
Has abstractyes

Explore more

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