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Record W4316618095 · doi:10.23865/noasp.149.ch1

Hvem styrte de nordiske byene ca. 1500–1800?

2022· book-chapter· en· W4316618095 on OpenAlexaboutno aff
Knut Dørum

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCompetitor analysisFeudalismGermanEconomyDanishGovernment (linguistics)GeographyEconomic historyPoliticsQuarter (Canadian coin)Early modern periodPolitical scienceHistoryEconomicsArchaeologyLawManagement

Abstract

fetched live from OpenAlex

Who governed the Nordic towns in c. 1500–1800? This book examines the political economy in Norway, Denmark (including the German-speaking provinces under Danish rule), Sweden, Finland, and the Baltic provinces that belonged to the Swedish Crown in the early modern period. It explores not only the institutions and people that governed or dominated the small and medium-sized towns in this northern region, but also seeks to detect how various types of towns functioned in terms of government and division of power and wealth. This book is inspired by the pivotal studies of Finn-Einar Eliassen in the late 1990s concerning the progression of family dynasties in ruling several small towns in Norway from c. 1600–1800. Eliassen maintained that ownership of the very ground upon which the town was built came to define a privatized lordship, not only in Norway but also in various peripheries in central and northern Europe. The long distances to the central government, along with growth in international trade and transnational commerce networks across the oceans, laid the foundation for what he has coined ‘small town feudalism’. The families who owned the town area took advantage of having the means to determine which individuals and families were permitted to establish themselves as merchants in the lucrative timber trade. As landlords they could refuse to rent out parcels of land attached to the houses in the town, thus rejecting unwanted competitors, and in this way, they were able to reserve the major share of trade and industry for themselves. This also implied the opportunity to establish patron-client relationships with many of the inhabitants and a dominant role in political and social affairs as well. The studies presented in our book show that ownership of the town area does not seem to be the key element in relation to the control or domination of a town and its hinterlands. This is in opposition to Eliassen’s model. We assert that the main fundament in privatized monopoly towns lay in the establishment of social networks, the ownership of strategic land estates in connection with trade, industry and transport, and, above all, controlling the credit system that bound, the peasants and other social groups to supply their masters with labour, lumber, agricultural products, and so on. This applies in particular to the small towns of Norway, where the emergence of privatized monopoly towns became most prevalent. Yet the power that the family dynasties exerted seems to have been limited when their tenants in the town transferred the right of renting and utilizing the land attached to their houses in connection with house sales. That implied the practice of permanent tenancy, allowing the tenant to sell his or her right to rent and use the parcel of land in the town. Furthermore, in the most privatized towns in Norway, the landlords had to let in competitors and tended to have a restricted capacity in regard to political authority and economic domination. In addition, their power basis turned out to be unstable and fragile. A scandal, several shipwrecks or money problems could ruin and tear down the ‘matador’ of a town. The many towns of the Nordic countries came under the strong influence of state government or larger networks of elites. However, in certain periods and situations, conditions allowed family dynasties or an exclusive elite throughout the Nordic countries to dominate the politics and business of the town to a great extent, regardless of the ownership of the land. This was more likely to happen in areas far from the great merchant companies and their privileges in the capital cities and larger towns, or far from the reach of the bureaucratic, centralized state. A peculiar phenomenon is the ‘company town’ – related to mining, shipyards and other industries – which could be found in all countries, especially in connection with mining in Sweden and Norway. Mining towns rose to be the most monopolized urban sites – either as state-run or private company towns. The company monitored all administrative, judicial and economic functions in the urban site. The tendencies of town feudalism in terms of family dynasties or the domination of elites must be seen as a consequence of a patrimonial society, based on personal ties between patrons and clients including strong social networks that rested upon marriage, kinship, political and economic friendship, and alliances.

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)0.001
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: none
Teacher disagreement score0.090
Threshold uncertainty score0.302

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0060.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0900.037

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 head0.038
GPT teacher head0.197
Teacher spread0.159 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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