Chronological objects in demographic research

Willekens, Frans

doi:10.4054/demres.2013.28.23

Cited by 10 publications

(3 citation statements)

References 20 publications

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“…The linkage was facilitated by the availability of information on the children's age at death, as registered by priests. Exact age was, however, ultimately calculated by matching the age at birth and death using day century coding, or counting the number of days since January 1, 1800 (Willekens 2013). The 'nolinkage rate' is the proportion of 'not found' dead children over the total number of dead, once we exclude the children born in a different parish (for details see Minello, Dalla-Zuanna, and Alfani 2017).…”

Section: Methodsmentioning

confidence: 99%

The growing number of given names as a clue to the beginning of the demographic transition in Europe

Minello¹,

Dalla‐Zuanna²,

Alfani³

2021

DemRes

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BACKGROUNDCultural factors are usually considered to have played a crucial role in the reduction in neonatal and infant mortality during the demographic transition; however, so far historical demographers have failed to produce precise measurements of their impact. This article introduces a new measure: the number of given names. We show the existence of a connection between the number of names given to a newborn and neonatal survival in 19 th -century Europe. METHODSThe article makes use of information from the CHILD database, focusing on six urban parishes in northeastern Italy, 1816-1865. We carried out a continuous-time event history analysis looking at neonatal transition to death. RESULTSWe show that the habit of assigning to the newborn a growing number of names spreads over time. Among the children with a single name neonatal mortality remains high and constant throughout the fifty years analyzed, while it halves among the children with two names and it decreases three times among children with three or more names. The kind of information we use is available also for other world areas, and we provide some evidence for this trend in France. CONTRIBUTIONWe interpret this as evidence of the spread of greater attention to children. We argue that it is possible to use the number of given names as an indicator of the spread of new practices and of the timing of their initial emergence, and as a measure of the ability of cultural factors to shape neonatal and infant mortality.

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Section: Methodsmentioning

confidence: 99%

The growing number of given names as a clue to the beginning of the demographic transition in Europe

Minello¹,

Dalla‐Zuanna²,

Alfani³

2021

DemRes

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“…We have linked birth certificates to death certificates for children born in the same parish who died at age 5 or younger, using as linkage keys name and surname of the child, name of the father, and name and surname of the mother. The linkage was facilitated by the availability of information on the children"s age at death, as registered by priests; exact age was, however, ultimately calculated by matching the age at birth and death using Day Century Coding, or counting the number of days since January 1 st , 1800 (Willekens 2013).…”

Section: Datamentioning

confidence: 99%

Mortality selection in the first three months of life and survival in the following thirty-three months in rural Veneto (North-East Italy) from 1816 to 1835

Piccione

Zuanna²,

Minello³

2014

DemRes

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BACKGROUNDA number of studies have examined the influence of life conditions in infancy (and pregnancy) on mortality risks in adulthood or old age. For those individuals who survived difficult life conditions, some scholars have found a prevalence of positive selection (relatively low mortality within the population), while others have observed the prevalence of a so-called scar-effect (relatively high mortality within the population). OBJECTIVEUsing micro-data characterized by broad internal mortality differences before the demographic transition (seven parishes within the region of Veneto, North-East Italy, 1816-35), we aim to understand whether children who survived high mortality risks during the first three months of life (early infant mortality) had a higher or a lower probability of surviving during the following 33 months (late infant mortality). METHODSUsing a Cox regression, we model the risk of dying during the period of 3-35 months of age, considering mortality level survived at age 0-2 months of age as the main explanatory variable. RESULTSWe show that positive selection prevailed. For cohorts who survived very severe early mortality selection (q 0-2 >400‰, where the subscripts are months of age), mortality

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“…In the context of the uncertainty of forecasts, predictability limits have been extensively discussed elsewhere (Keyfitz 1981; Keilman's contribution to Willekens 1990;de Beer 2000;Bijak 2010), with two main methodological conclusions. Firstly, it is argued that demography should embrace uncertainty more closely (Alho and Spencer, 2005), in particular by moving from traditional deterministic projections to probabilistic forecasts.…”

Section: Motivation: Meet the Beastmentioning

confidence: 99%

Feeding the beast: Can computational demographic models free us from the tyranny of data?

2011

ECAL 2011: The 11th European Conference on Artificial Life

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Since its inception, ALife has moved from producing large numbers of highly-idealised, theoretical models towards greater integration with empirically collected data. In contrast, demography -the interdisciplinary study of human populations -has been largely following the principles of logical empiricism, with models driven mainly by data, and insufficient attention being paid to theoretical investigation. Such an approach reduces the ability to produce micro-level explanations of population processes, which would be coherent with the phenomena observed at the macro level, without having to rely on ever-increasing data demands of complex demographic models. In this paper we argue that by bringing ALife-inspired, agent-based methods into demographic research, we can both develop a greater understanding of the processes underlying demographic change, and avoid a limiting over-dependence on potentially immense sets of data.-But you are paying a lot of money for the dragon! -And what, should we just give it to the citizens instead? [...] I see you know nothing about the principles of economics! Export credit warms up the economy and increases the global turnover.-But it also increases the dragon as such -I stopped him. -The more intensely you feed him, the bigger he gets; and the bigger he gets, the higher his appetite. What kind of a calculation is it? He will finally devour you all!

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Chronological objects in demographic research

Cited by 10 publications

References 20 publications

The growing number of given names as a clue to the beginning of the demographic transition in Europe

The growing number of given names as a clue to the beginning of the demographic transition in Europe

Mortality selection in the first three months of life and survival in the following thirty-three months in rural Veneto (North-East Italy) from 1816 to 1835

Feeding the beast: Can computational demographic models free us from the tyranny of data?

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