MétaCan
Menu
Back to cohort
Record W7150389894

Farmers in Delfzijl from the sixteenth to the early twentieth centuries::tenants and freeholders

2017· book-chapter· W7150389894 on OpenAlexaboutno aff
Richardus; id_orcid 0009-0006-1804-7642 Paping

Bibliographic record

VenueUniversity of Groningen research database (University of Groningen / Centre for Information Technology) · 2017
Typebook-chapter
Language
FieldEconomics, Econometrics and Finance
TopicFinancial Crisis of the 21st Century
Canadian institutionsnot available
Fundersnot available
KeywordsFreeholdAgricultureEconomic rentEliteLand tenureReservationQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

The chapter gives a general description of the quantitative development of agriculture over the very long run in the former municipality of Delfzijl (Groningen, the Netherlands), discussing the development of the number of farmers, farm-size, land ownership and the market price of agricultural land. Special attention is given to the fact that this region stands out in the province of Groningen for its relatively extremely large share of freeholders in the eighteenth century controlling up to 40% of the land. The chapter shows that these farms were not successors of medieval freehold farms. Nearly all large freehold farms came into existence in the second half of the seventeenth century or the early eighteenth century, when tenant farmers bought the ownership of land, usually from nobles or others belonging to elite groups. This was possible because of the extreme low prices in this period in the region, partly due to agricultural hardships related to persistent local water problems. Because of the low land rents and the high risks of extra costs for owners due to for instance the maintenance of dikes, investing in land around Delfzijl was no longer interesting. Consequently, a part of the more well-to-do local tenant farmers could buy their land for extremely low prices.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0030.003
Scholarly communication0.0000.003
Open science0.0050.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.231
Teacher spread0.187 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of Groningen research database (University of Groningen / Centre for Information Technology)Same topicFinancial Crisis of the 21st CenturyFrench-language works237,207