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Record W1587001545

The Long View: Labour Productivity, Labour Income and Living Standards in Canada

2002· preprint· en· W1587001545 on OpenAlexaboutno aff
Tony Fisher, Doug Hostland

Bibliographic record

VenueRePEc: Research Papers in Economics · 2002
Typepreprint
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsLabour economicsProductivityStandard of livingDepreciation (economics)Income sharesInvestment (military)Profit (economics)Income distributionInvestment goodsWage shareMeasures of national income and outputConsumption (sociology)Human capitalCapital formationMarket economyProduction (economics)MacroeconomicsFinancial capitalWageInequalityEfficiency wage
DOInot available

Abstract

fetched live from OpenAlex

In this chapter, Tony Fisher and Doug Hostland provide an historical perspective on trends in labour productivity, labour income and living standards in Canada. They find that, once the appropriate adjustments are made, the labour share and the non-labour share (composed of profits, interest and investment income, and incorporated business income) in national income tend to revert to their historical means over the 1926-2001 historical period, although divergences may last for several years. They note, for example, that the decline in the labour share in Canada since 1994 has not been due to any increase in profit share, but to an increase in the share of depreciation or capital consumption allowances associated with the short services lives of high-tech investment goods.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.509

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0050.003
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.328
Teacher spread0.303 · 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

Citations8
Published2002
Admission routes1
Has abstractyes

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