Bibliographic record
Abstract
By 1950, the trunk networks in railways, telegraph and telephone were owned and operated throughout western Europe by state monopoly enterprises, which, in some countries, also operated the secondary lines. Much of their economic environment was determined not by arm's- length regulation of fares, rates and supply conditions, but by policies established with their supervising ministries (of transport, communications etc.) and ultimately determined by parliaments. How these policies affected profitability and productivity is evaluated in chapter 14. Here I am more concerned with examining how technological change affected the institutional setting. In the case of telecommunications, it was the advent of microprocessors and the development of information technology that transformed a simple industry (telephone at the end of a network) into one with complex facilities for transmitting information via computers, mobiles, fax, videotex and email. This was to come in the last quarter of the century. Before that came the revolutions in road and air transport. Airline business was small beer in the late 1940s, but by the 1970s had become a major industry, especially on the passenger side. The wide-bodied, large-capacity aircraft that emerged in the late 1950s had, eventually, a big effect on shipping in Europe and some effect on railways, though nothing like the impact on rail in the USA. The competition from road transport had started in the inter-war period and, especially on the passenger side, developed fiercely after 1950 as cheaper and more reliable vehicles entered the market.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".