The European Society of Historical Demography (ESHD) is pleased to invite submissions for its 7th Conference, to be held in Paris from 8 to 11 September 2027. This event aims to provide a platform for scholars and researchers to present their latest findings and to encourage discussions on a wide array of topics in historical demography.
Contributions across the entire discipline of historical demography are welcomed. These may include any key topics such as family systems, family dynamics and individual life courses; marriages and partner selection; networks and alliances, migration and mobility; health and mortality; and fertility and reproductive behaviour. More broadly, we welcome all papers taking an historical perspective to study the effects of changing social, economic, political, institutional, and environmental conditions on demographic behaviour and population dynamics. Papers employing innovative methodologies, comparative analyses, or interdisciplinary perspectives are particularly encouraged.
Only one proposal per person as first author/presenter will be accepted.
Full sessions (four or five papers) are also welcome. Each paper must be submitted individually, indicating the name of the session and the organizer(s) in the dedicated field within the submission form.
Paper proposals can only be submitted at the Conference website (https://eshd2027.eshd.eu/) by filling the submission form. Submission guidelines and further information regarding deadlines can be found on the conference website.
The deadline for submitting a paper proposal and pre-registration is January 31, 2027. Information on the acceptance of submission will be sent by March 31, 2027. Early bird registration will end on June 20, 2027.
The theme of this year’s conference is:
Automated methods and big data in Historical Population Research
The theme of this year’s conference, aims at addressing the deep transformations of the field produced by the exponential developments of AI and automated methods in accessing and processing historical sources to study past populations. As elsewhere, in the academia and beyond, these developments already have a considerable impact on the practices and methods of historical demography by radically altering access to historical sources, through, among many others, text extraction and character recognition; automated data processing and coding of information; automated linking of sources and individuals.
Indeed, the production, development, and processing of large-scale datasets has been at the core of historical demography since its inception. As a result, there is no question that the recent technological evolutions offer many opportunities to advance our knowledge of past societies. The most visible benefit is certainly the increasing ease of access to a large variety of archival sources. But it goes well beyond that, with the processing of the datasets extracted from the historical sources as well as the increasing use of AI for all stages of the research process. To some extent, it is a self-reinforcing process, as automated methods produce massive amounts of data, that themselves need new and automated systems to be processed. The multifaceted nature of the change might have strong implications for the evolution of the field in the coming years.
There are also clear limitations and considerable risks associated with the massive use of these new technologies (again limiting to the field of historical demography). The technical skills necessary to take advantage of the new methods might reduce the social science component of the field and further tilt the balance towards computer technologies. It might certainly reduce the degree of interdisciplinarity in the field; shift it from humanities to computer sciences; and intensify the gap between historians and demographers. The focus on sources easily accessible and already digitized could end up developing more blind spots. The huge amount of data produced from historical sources will soon raise questions that historical demographers have until now avoided asking: on privacy, on ownership, on resource usage.
The invited keynote speakers will collectively offer ample and varied perspectives on the transformations of historical demography introduced by large language models and other AI-related tools. But we hope that submitted papers to the conference can also contribute to the discussion. In particular, in addition to papers presenting various usage of these new tools, we expect to receive contributions aiming for a critical perspective on the recent (and future) transformations of the field.
Source: ESHD.
