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Record W2907343408 · doi:10.1787/745662258480

Plant Turnover and Productivity Growth in Canadian Manufacturing

2002· report· en· W2907343408 on OpenAlexaffabout
John R. Baldwin, Wulong Gu

Bibliographic record

VenueOECD science, technology and industry working papers · 2002
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsProductivityForestryGeographyEconomics

Abstract

fetched live from OpenAlex

Les entrees sur le marche sont importantes parce que les nouvelles entreprises et les nouvelles usines, qui generent de nouveaux produits et de nouvelles technologies, font une vive concurrence aux enterprises existantes. Dans le present document, nous examinons l’importance du roulement des usines dans le secteur manufacturier canadien, c’est-a-dire le nombre d’entrees et de sorties, au cours des trois dernieres decennies, soit de 1973 a 1979, de 1979 a 1988 et de 1988 a 1997. Nous examinons aussi la contribution de ce roulement a la croissance de la productivite du travail dans le secteur manufacturier au cours de ces trios periodes. Le roulement des usines contribue de facon importante a la croissance de la productivite, les usines entrantes plus productives remplacant les usines sortantes moins productives. Par ailleurs, nous constatons qu’une part disproportionnellement elevee de l’effet des entrees et des sorties sur la croissance de la productivite est attribuable a la ...

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.038
GPT teacher head0.222
Teacher spread0.184 · 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 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

Citations16
Published2002
Admission routes2
Has abstractyes

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