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Record W3125431182

Plant Turnover and Productivity Growth in Canadian Manufacturing

2002· preprint· en· W3125431182 on OpenAlex
John R. Baldwin, Wulong Gu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRePEc: Research Papers in Economics · 2002
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsProductivityManufacturing sectorCompetition (biology)Total factor productivityPolitical scienceWelfare economicsEconomicsEconomyInternational economicsEconomic growthEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Entry is important because new firms and new plants provide an important source of competition to incumbents. They are a source of new products and technologies. In this article, we outline the size of the turnover in plants that have entered and exited the Canadian manufacturing sector over each of three periods--1973--1979, 1979--1988, and 1988--1997. We also examine the contribution of plant turnover to labor productivity growth in the manufacturing sector over the three periods. Plant turnover makes a significant contribution to productivity growth as more productive entrants replace exiting plants that are less productive. We also find that a disproportionately large fraction of the contribution of plant turnover to productivity growth is due to multi-plant or foreign-controlled firms closing down and opening up new plants. The plants opened up by multi-plant or foreign-controlled firms are typically much more productive than those opened by single-plant or domestic-controlled firms. Copyright 2006, Oxford University Press.

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.044
GPT teacher head0.253
Teacher spread0.209 · 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