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Record W2337784462

Productivity Trends in the Canadian Transport Sector: An Overview

2016· preprint· en· W2337784462 on OpenAlexaboutno aff
Matthew Calver, Fanny McKellips

Bibliographic record

VenueRePEc: Research Papers in Economics · 2016
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityAgricultural economicsTruckMultifactor productivityBusinessEconomicsEconomic growthEngineeringTotal factor productivity
DOInot available

Abstract

fetched live from OpenAlex

In recent decades, the overall growth in productivity of many subsectors of the Canadian transportation and warehousing sector has been above average. In particular, while labour productivity (real GDP per worker) grew an average of 0.64 per cent per year between 2000 and 2014 in the transportation and warehousing sector, labour productivity grew an average of 1.83 per cent per year in the truck transportation subsector, 3.25 per cent per year in the air transportation subsector and 2.09 per cent in the train transportation subsector for the same period. Conversely, in the urban transit subsector, labour productivity decreased an average of 0.76 per cent per year between 2000 and 2014. This report provides a detailed analysis of output, input and productivity trends in four subsectors of the Canadian transportation and warehousing sector. It also examines drivers of the productivity growth for each subsector as well as policies that could enable faster growth. Given the impact that the transportation sector has on many Canadian industries as well as the Canadian economy, maintaining productivity growth is important.

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)0.003
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 score0.695
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.082
GPT teacher head0.307
Teacher spread0.225 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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