The term technological fix, coined by technologist/administrator Alvin Weinberg in 1965, vaunted engineering innovation as a generic tool for circumventing problems commonly conceived as social, political, or cultural. A longtime Director of Oak Ridge National Laboratory, government consultant, and essayist, Weinberg also popularized the term big science to describe national goals and the competitive funding environment after the Second World War. Big science reoriented towards technological fixes, he argued, could provide a new "Apollo project" to address social problems of the future. His ideas-most recently echoed in "solutionism"-have channeled confidence and controversy ever since. This article traces the genesis and promotion of the concept by Weinberg and his contemporaries. It argues that, through the concept, the marginal politics and technological confidences of interwar scientists and technocrats were repositioned as mainstream notions closer to the heart of big science policy.
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http://dx.doi.org/10.1353/tech.2018.0061 | DOI Listing |
Eur J Neurol
February 2025
Nuffield Department of Women's and Reproductive Health, Medical Science Division, University of Oxford, Oxford, UK.
Background And Purpose: This study aims to assess the disease burden and care quality along with cross-country inequalities for stroke at global, regional, and national levels from 1990 to 2021.
Methods: Data on stroke were extracted from the Global Burden of Disease (GBD) study 2021 for the globe, five sociodemographic index (SDI) regions, 21 GBD regions, and 204 countries/territories. The disease burden was quantified using the age-standardized disability-adjusted life years rate (ASDR).
J Biol Rhythms
January 2025
Shiu Chien-Gene Lay Department of Bioengineering, University of California, San Diego, La Jolla, California.
The nature of biological research is changing, driven by the emergence of big data, and new computational models to parse out the information therein. Traditional methods remain the core of biological research but are increasingly either augmented or sometimes replaced by emerging data science tools. This presents a profound opportunity for those circadian researchers interested in incorporating big data and related analyses into their plans.
View Article and Find Full Text PDFComput Methods Biomech Biomed Engin
January 2025
School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, Changzhou University, Changzhou, P.R. China.
Slow eye movements (SEMs) are a reliable physiological marker of drivers' sleep onset, often accompanied by EEG alpha wave attenuation. A parallel multimodal 1D convolutional neural network (PM-1D-CNN) model is proposed to classify SEMs. The model uses two parallel 1D-CNN blocks to extract features from EOG and EEG signals, which are then fused and fed into fully connected layers for classification.
View Article and Find Full Text PDFNiger Med J
January 2025
Department of Epidemiology & Community Health, University of Ilorin, Nigeria.
Background: Sleep is a very important physiologic process which is necessary to maintain a state of well-being. Obstructive Sleep Apnea (OSA) is prevalent among all age groups with variations in presentation and severity. It is often underreported, especially among young people in the Low- and Middle-Income Countries LMICs.
View Article and Find Full Text PDFTob Induc Dis
January 2025
Institute of Health and Environment, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea.
Introduction: Smoking behaviors can be quantified using various indices. Previous studies have shown that these indices measure and predict health risks differently. Additionally, the choice of measure differs depending on the health outcome of interest.
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