Recent research promotes comparing the current state of the environment with the past (and not the future) to increase the pro-environmental attitudes of those on the political right. We aimed to replicate this temporal framing effect and extend on research in this area by testing the potential drivers of the effect. Across two large-scale replication studies, we found limited evidence that past comparisons (relative to future comparisons) increase pro-environmentalism among those with a more conservative political ideology, thus precluding a full investigation into the mediators of the effect. Where the effect was present, it was not consistent across studies. In Study One, conservatives reported greater certainty that climate change was real after viewing past comparisons, as the environmental changes were perceived as more certain. However, in Study Two, the temporal framing condition interacted with political orientation to instead undermine the certainty about climate change among political liberals in the past-focused condition. Together, these studies present the first evidence of backfire from temporal frames, and do not support the efficacy of past comparisons for increasing conservatives' environmentalism. We echo recent calls for open science principles, including preregistration and efforts to replicate existing work, and suggest the replication of other methods of inducing temporal comparisons.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877654 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0246058 | PLOS |
Alzheimers Dement
December 2024
University of Washington, Seattle, WA, USA.
Background: The BRAIN Initiative has stimulated development of novel single cell and spatial molecular approaches to understand human brain structure and function. However, traditional methods for human brain specimen collection, including retrospective archival tissues, have not been optimized for these latest methods. A modernized approach that optimizes tissue quality, anatomical precision, and comprehensive, quantitative neuropathological assessments is needed to maximize the impact of the tremendous investment and remarkable technological advances in human neuroscience research.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Background: Neuron loss exceeds tau tangle formation (Gomez-Isla et al. 1997) and p-tau vulnerability differs by layer and subfield in entorhinal cortex (Llamas-Rodriguez et al., 2022).
View Article and Find Full Text PDFNat Commun
January 2025
State Key Laboratory of Membrane Biology, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China.
Camera-based single-molecule techniques have emerged as crucial tools in revolutionizing the understanding of biochemical and cellular processes due to their ability to capture dynamic processes with high precision, high-throughput capabilities, and methodological maturity. However, the stringent requirement in photon number per frame and the limited number of photons emitted by each fluorophore before photobleaching pose a challenge to achieving both high temporal resolution and long observation times. In this work, we introduce MUFFLE, a supervised deep-learning denoising method that enables single-molecule FRET with up to 10-fold reduction in photon requirement per frame.
View Article and Find Full Text PDFSci Adv
January 2025
Department of Bio and Brain engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Nocturnal and crepuscular fast-eyed insects often exploit multiple optical channels and temporal summation for fast and low-light imaging. Here, we report high-speed and high-sensitive microlens array camera (HS-MAC), inspired by multiple optical channels and temporal summation for insect vision. HS-MAC features cross-talk-free offset microlens arrays on a single rolling shutter CMOS image sensor and performs high-speed and high-sensitivity imaging by using channel fragmentation, temporal summation, and compressive frame reconstruction.
View Article and Find Full Text PDFFront Public Health
December 2024
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Objective: To characterize the public conversations around long COVID, as expressed through X (formerly Twitter) posts from May 2020 to April 2023.
Methods: Using X as the data source, we extracted tweets containing #long-covid, #long_covid, or "long covid," posted from May 2020 to April 2023. We then conducted an unsupervised deep learning analysis using Bidirectional Encoder Representations from Transformers (BERT).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!