Projectdetails
Beschrijving
This proposal argues that the four most used and most up-to-date population estimates for the Low Countries (the area more or less covered by the Netherlands, Belgium, and Luxembourg) for the period prior to 1800 are imprecise, often inaccurate, and generally inconsistent. By using the same research protocols and primary sources, but with added information on the context of the censuses and their geographic coverage, we will replicate these four studies. This will lead to significantly improved local, provincial, and national population estimates, benefitting a wide range of scholars from economists to experts on development studies.
The project will revert to the same primary sources, but for the first time will use the unaggregated village-level data collected in these premodern censuses to produce more accurate and precise population figures. A newly developed GIS dataset of premodern local parish-level boundaries in the Low Countries will act as a visual control mechanism, much in the same way previous scholars have used lists of villages or their own local knowledge to account for missing areas. A new typology of premodern censuses will dramatically improve the quality and comparability of population estimates in the Low Countries.
Beschrijving in lekentaal
| Korte titel | (Re)counting the uncounted |
|---|---|
| Status | Geëindigd |
| Effectieve start/einddatum | 01/09/2020 → 31/12/2022 |
Vingerafdruk
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Linked Data for modelling and replicating the knowledge production process in data-driven humanities research
Stapel, R. & Zandhuis, I., jan. 2025, In: Digital Scholarship in the Humanities. 40, Supplement 1, blz. i100-i107 8 blz.Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgave › Artikel › Wetenschappelijk › peer review
Open Access -
Replication studies in the Netherlands: Lessons learned and recommendations for funders, publishers and editors, and universities
Derksen, M., Meirmans, S., Brenninkmeijer, J., Pols, J., de Boer, A. R., van Eyghen, H., Gayet, S., Groenwold, R., Hernaus, D., Huijnen, P., Jonker, N., de Kleijn, R., Kroll, C. F., Krypotos, A.-M., van der Laan, L. N., Luijken, K., Meijer, E., Pear, R. S. A., Peels, R. & Peeters, R. & 5 anderen, , 13 aug. 2024, (E-pub ahead of print) In: Accountability in Research. 19 blz.Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgave › Artikel › Wetenschappelijk › peer review
Open AccessBestand53 Downloads (Pure) -
Conflating Historical Population Statistics Using a Historical GIS with a Flexible Semantic Model for Premodern Administrative Units in the Low Countries: The (Re)counting the Uncounted and Historical Atlas of the Low Countries Projects
Stapel, R., 13 nov. 2023, blz. 56-59.Onderzoeksoutput: Bijdrage aan conferentie › Paper › Wetenschappelijk › peer review
Open Access3 Citaten (Scopus)
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Replicatie bevolkingsschattingen voor de 14e tot 19e eeuw voor Nederland en België
Stapel, R. (Speaker)
09 dec. 2025Activiteit: Toespraak of presentatie › Maatschappelijk
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A Fine-Grained Population Reconstruction of the Low Countries (14th Century-Present)
Stapel, R. (Speaker)
11 sep. 2025Activiteit: Toespraak of presentatie › Academisch
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The Problem of Spatial and Source Consistency in Premodern Population Estimates. Strategies Applied in the Case of the Low Countries, 1350-1800
Stapel, R. (Speaker)
31 jul. 2025Activiteit: Toespraak of presentatie › Academisch
Datasets
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'(Re)counting the Uncounted': Documentation and Instructions
Stapel, R. (Maker), IISH Dataverse, 08 apr. 2023
https://hdl.handle.net/10622/HWDA3Z
Dataset
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'(Re)counting the Uncounted': Catalogue and Typology of Premodern Censuses in the Low Countries
Stapel, R. (Maker), Flens, I. (Maker), Vaccari, D. (Maker) & Versmissen, R. (Maker), IISH Dataverse, 08 apr. 2023
https://hdl.handle.net/10622/4FWVNL
Dataset
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'(Re)counting the Uncounted': Repository of Digitised Premodern Censuses in the Low Countries
Stapel, R. (Maker), Flens, I. (Maker), Vaccari, D. (Maker) & Versmissen, R. (Maker), IISH Dataverse, 08 apr. 2023
https://hdl.handle.net/10622/E5BC1Y
Dataset