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Record W2887964976 · doi:10.4337/9781785366062.00009

Regional economic impacts of a transportation infrastructure project: the Herb Gray Parkway

2018· book-chapter· en· W2887964976 on OpenAlexaboutno aff
Hanna Maoh, Charles Burke

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2018
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsWindsorPurchasingGray (unit)Regional scienceMultiplier (economics)EconomicsGeographyBusinessOperations managementEnvironmental scienceMacroeconomics

Abstract

fetched live from OpenAlex

This chapter presents estimates of total employment impacts at both the regional and national levels for the Herb Gray Parkway construction project in Windsor, Ontario, Canada. Because this study is based on detailed quarterly employment and purchasing data provided by the contractor, it generates more specific and accurate estimates than conventional input-output and other multiplier methods. The ex post estimates are contrasted with higher ex ante estimates and reasons for the gap between the two are explained. This yields insight into why anticipated employment impacts may be over-estimated and provides guidelines for more realistic impact projections. The chapter also addresses the question of what long-term regional structural transformations may arise from capital formation, skills development, technology transfer and other processes.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.209
Teacher spread0.190 · 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 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
Published2018
Admission routes1
Has abstractyes

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