Lecture

Sciences and Technologies Studies: Commensurable Data

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Description

This lecture explores the extension of 'The Topofil of Boa Vista' by B. Latour in Sciences and Technologies Studies, focusing on the transition from case studies to commensurable data. It discusses the observation of soil and plants as indicators, the reconstitution of the forest in a cupboard, and the diagram of the soil. The lecture also delves into the production of scientific facts, the role of social sciences in computability, and the importance of comparisons and indicators in digital humanities.

Official source

Related concepts (32)

Computable function

Computable functions are the basic objects of study in computability theory. Computable functions are the formalized analogue of the intuitive notion of algorithms, in the sense that a function is computable if there exists an algorithm that can do the job of the function, i.e. given an input of the function domain it can return the corresponding output. Computable functions are used to discuss computability without referring to any concrete model of computation such as Turing machines or register machines.

Computable number

In mathematics, computable numbers are the real numbers that can be computed to within any desired precision by a finite, terminating algorithm. They are also known as the recursive numbers, effective numbers or the computable reals or recursive reals. The concept of a computable real number was introduced by Emile Borel in 1912, using the intuitive notion of computability available at the time. Equivalent definitions can be given using μ-recursive functions, Turing machines, or λ-calculus as the formal representation of algorithms.

Computability theory

Computability theory, also known as recursion theory, is a branch of mathematical logic, computer science, and the theory of computation that originated in the 1930s with the study of computable functions and Turing degrees. The field has since expanded to include the study of generalized computability and definability. In these areas, computability theory overlaps with proof theory and effective descriptive set theory.

Computability

Computability is the ability to solve a problem in an effective manner. It is a key topic of the field of computability theory within mathematical logic and the theory of computation within computer science. The computability of a problem is closely linked to the existence of an algorithm to solve the problem. The most widely studied models of computability are the Turing-computable and μ-recursive functions, and the lambda calculus, all of which have computationally equivalent power.

Scientific theory

A scientific theory is an explanation of an aspect of the natural world and universe that can be (or a fortiori, that has been) repeatedly tested and corroborated in accordance with the scientific method, using accepted protocols of observation, measurement, and evaluation of results. Where possible, theories are tested under controlled conditions in an experiment. In circumstances not amenable to experimental testing, theories are evaluated through principles of abductive reasoning.

Related lectures (32)

Recursive Enumerability: Turing Machines and Undecidable Languages

Covers recursively enumerable languages, Turing machines, and the construction of undecidable languages.

Universal Turing Machine: Definition and Functioning

Explores the universal Turing machine, its canonical representation, and its role in defining algorithms and theoretical computer science concepts.

Numerics: semester project

Covers the semester project on numerics, focusing on adaptive algorithms and multistep methods.

Communication Amid Uncertainty

Explores challenges in human communication, context importance, compression problems, uncertain functionality, and proof verification.

The Social Nature of Research Work