North American freight rail: regulatory evolution, strategic rejuvenation, and the revival of an ailing industry
Bibliographic record
Abstract
North American railways were crucial to the integration of \t\t\t\tnational territories from the mid-1850s through the 1920s. In \t\t\t\tthe US, Canada, and Mexico, their development supported \t\t\t\tpopulation settlement, resource extraction, industrialization, \t\t\t\tand the expansion of markets to regional and national spatial \t\t\t\tscales. From the 1920s, rail's dominance in transportation \t\t\t\tdeclined as highways and trucking developed. Strict railway \t\t\t\tregulation and direct government ownership, motivated by earlier \t\t\t\trail firm abuses, limited railways' strategic adjustment to \t\t\t\ttrucking competition and aggravated the problems of falling \t\t\t\trevenue and decreasing profitability. From the 1970s, however, a \t\t\t\tdramatic shift began as three prongs of economic liberalization \t\t\t\twere implemented: deregulation of the industry, privatization of \t\t\t\tstate-owned firms, and the liberalization of controls on foreign \t\t\t\tdirect investment.\nThis dissertation characterizes the liberalized governance \t\t\t\tregimes that have emerged, evaluates changes in the industrial \t\t\t\tand geographic organization of the freight rail industry, and \t\t\t\texamines significant episodes of regional rail restructuring \t\t\t\tinvolving the dominant Class I firms. Shifts in governance are \t\t\t\texamined by outlining pre-reform regulatory regimes in the US, \t\t\t\tCanada, and Mexico, then discussing the step-wise sequence of \t\t\t\tchanges enacted in each country that significantly reduced \t\t\t\trestrictions on freight rail firms' business options (Chapter \t\t\t\tIII). Liberalized governance enabled changes in the industry's \t\t\t\torganization, including its firm-size distribution, \t\t\t\tprivatization of state-owned firms, and consolidation, as firms \t\t\t\temployed hitherto restricted strategies to restructure their \t\t\t\tassets and activities (Chapters III and IV).\nCase studies of regional restructuring, designed to highlight the \t\t\t\tinterplay of regulatory governance, intra-industry competition, \t\t\t\tand firm strategies, include: the consolidation of firms in the \t\t\t\tEastern US and the privatization of Conrail (Chapter V); the \t\t\t\tconsolidation of firms in the Western US and the impact of \t\t\t\tincreased rail container traffic on infrastructure and \t\t\t\toperations (Chapter VI); the expansion of freight rail \t\t\t\townership, investment, and traffic patterns integrating the \t\t\t\tNAFTA countries (Chapter VII); and comparison of the strategies \t\t\t\tadopted by CPR and CN, the dominant Canadian firms (Chapter \t\t\t\tVIII).\nResearch materials included official and trade organization \t\t\t\tstatistics, corporate reports, the trade press, and mapping \t\t\t\tdatasets of rail lines. Numerous maps illustrate the changing \t\t\t\tgeography of the North American freight rail industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".