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Record W2949116815

Chapter 2. Why Productivity Matters

2008· book-chapter· fr· W2949116815 on OpenAlexaboutno aff
Tom Brzustowski

Bibliographic record

VenueOpenEdition (OpenEdition) · 2008
Typebook-chapter
Languagefr
FieldEconomics, Econometrics and Finance
TopicItaly: Economic History and Contemporary Issues
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityNatural resource economicsEconomicsMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Productivity is like the weather—everybody talks about it, but nobody does anything. Of course, Canadians know what weather is. (with apologies to Mark Twain) What is productivity and why does it matter? Here is the definition posted on the website of Canada’s Department of Finance: “Productivity or Total Factor Productivity: The efficiency with which people and capital are combined in the output of the economy. Productivity gains lead to improvements in the standard of living, because as lab...

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), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.018
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0630.050

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 head0.038
GPT teacher head0.200
Teacher spread0.162 · 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; both teacher heads agree on what is shown here.

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
Published2008
Admission routes1
Has abstractyes

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