Project description
Navigating the currents of culture
In the currents of cultural evolution, the fate of written artefacts hangs on the delicate balance between cultural preferences and chance. How do texts, like living organisms, experience a process of preservation, transformation or extinction? To answer this question, the ERC-funded LostMA project will blend AI, complexity science and philological expertise to unravel the mysteries behind the deviation of textual transmission from pure chance. Focusing on chivalric literature in a European context, the team utilises deep learning for large-scale data collection on 4 000 documents. This groundbreaking approach not only scrutinises the transmission of texts but also challenges the role of chance in shaping cultural canons.
Objective
LostMa aims at understanding how human cultures are constituted and evolve, through the question of the transmission of written cultural artefacts. It strives to establish in what measure the transmission (and subsequent preservation or loss) of written artefacts, texts and ideas deviates from pure chance, and, if it deviates, by how much and why it does. It will do so by analysing the way that texts in manuscript form were copied, transformed or destroyed, in a similar way to the evolution of living organisms or of language variants, through process of innovation/mutation, fixation or extinction.
As such, the goal of this project is not only to understand the processes behind the transmission of texts, but also to grasp the extent to which humans are the actors of the transmission of their own culture and how much the survival of texts or the constitution of cultural canons are due to chance.
If this notion may seem provocative to humanities researchers, evolutionary biologists have long discovered the role of random drift in the survival or extinction of genetic traits and species.
To investigate this question, this project will attempt a paradigm-shift in philological methods, by combining artificial intelligence, complexity science and philological expertise. Stochastic birth-and-death processes and computer multi-agent simulations will be used to emulate the process of textual transmission.
A case study will be taken, regarding chivalric literature in European context. Supported by deep learning methods, large-scale data collection will be made on a corpus of 4000 documents in Romance, Germanic and Celtic languages, with a full-text zoom on approx. 1000 Old French manuscripts. Data will provide observable values to be compared to simulation results, in order to measure deviations from chance, make inferences on non observable values such as loss/survival rates of works and manuscripts, and understand the dynamics at work behind the transmission of texts.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been validated by the project's team.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been validated by the project's team.
- humanities history and archaeology history medieval history
- natural sciences biological sciences evolutionary biology
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- humanities languages and literature literature studies history of literature
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2023-STG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
75002 Paris
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.