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Record W7014164902

Pienet höyrylaivat Suomen ja erityisesti Kainuun sisävesiliikenteessä 1870-luvulta 1960-luvulle

2016· dissertation· en· W7014164902 on OpenAlexaboutno aff

Bibliographic record

VenueJyväskylä University Digital Archive (University of Jyväskylä) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration, Policy, and Dickens Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)CraftPeriod (music)Natural (archaeology)Rail network
DOInot available

Abstract

fetched live from OpenAlex

The significance in Finland of shipping on inland waterways has been great. This is due to the topography of the country with its many lakes and to the fact that the vast waterways in their natural state were easily navigable. The construction of canals resulted in even more extensive interconnected inland waterways. This study explores the tasks of the steamships plying these internal waterways, their numbers and significance, and also changes and the reasons for these between different inland waterways, as regards different types of vessels and shipowners in the period from the 1870s to the 1960s. Special attention is paid to steamships smaller than 19 net register tons. This limit was chosen because it was unusual for those smaller vessels to be included in the records kept by officialdom. The share of such small craft in inland waterway traffic as a whole was not generally noted. The present study refers to these individually as micro vessels and collectively as micro tonnage. It is known that 1870 there were 64 steamships afloat on inland waterways, of which approximately half were micro vessels. This number increased until in around 1930 it peaked at over 900. Two-thirds of these were micro vessels. Thereafter their number decreased, with 270 steamers still afloat in 1960, mostly micro tonnage. In the 1960s the use of these for economic purposes ceased almost completely. The number of passenger steamers was at its peak around the 1910s, but decreased thereafter as the transportation of passengers and freight was increasingly transferred from passenger vessels to the railways and later also to the roads. The share of micro tonnage of passenger vessels was just less than half. Of the freight carrying vessels, which at their greatest numbered 200, only few were micro vessels. In the 1900s tugboats generally comprised at least half of the steamships plying on inland waterways. Most of these were micro tonnage and as of the 1920s ninety per cent. The reason for this is obvious: the main characteristic of these vessels was not their capacity but their power, how much they could tow. Throughout the research period towing timber was the main concern in inland shipping. From the remote regions, where forestry was the main occupation, timber could generally be transported to the industrial plants only by floating it, mostly with the help of micro tonnage. Just over half of the passenger vessels were owned by private companies, but the small passenger vessels in particular were frequently owned by private entrepreneurs or others. Freight carrying vessels were owned by entrepreneurs but toward the end of the period studied also by industrial concerns. Most of the tugboats were owned either by companies in the forest industry or by timber floating concerns formed by sawmills.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.004

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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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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