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Record W2600258002

New Evidence on the Canada-U.S. ICT Investment Gap, 1976-2014 Selected OECD Countries, 1986-2013

2016· preprint· en· W2600258002 on OpenAlexaboutno aff
Jasmin Thomas

Bibliographic record

VenueRePEc: Research Papers in Economics · 2016
Typepreprint
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)ProductivityInformation and Communications TechnologyFellRecessionBusinessDemographic economicsEconomicsAgricultural economicsEconomic growthGeographyPolitical scienceCartographyMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Productivity growth results in part from investment in information and communications technologies (ICT). To better understand Canada’s poor productivity growth relative to the United States since 2000, this report provides a detailed examination of ICT investment trends in the two countries. The report finds that real ICT investment in the total economy in Canada has yet to recover from the 2008-2009 recession, while it has not suffered the same fate south of the border. Between 2008 and 2014 real ICT investment in Canada fell 1.0 per cent per year, compared to a 2.9 per cent per year increase in the United States. The gap was even greater for real ICT investment per job, down 1.8 per cent per year in Canada versus a 2.8 per cent annual increase in the United States. The weaker ICT investment growth in Canada resulted in a large increase in the Canada-US ICT investment gap from 31.6 percentage points to 43.7 points, as nominal ICT investment per job fell from 68.4 per cent of the US level in 2008, the highest value ever achieved, to 56.3 per cent in 2014.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.343
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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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