Hasil untuk "History America"

D. Rodrik

F. Knowles, L. Lovern

Angela R. Gover, Shannon B. Harper, L. Langton

Coronavirus Disease 2019 (COVID-19) is believed to have emerged in Wuhan, China in late December 2019 and began rapidly spreading around the globe throughout the spring months of 2020. As COVID-19 proliferated across the United States, Asian Americans reported a surge in racially motivated hate crimes involving physical violence and harassment. Throughout history, pandemic-related health crises have been associated with the stigmatization and “othering” of people of Asian descent. Asian Americans have experienced verbal and physical violence motivated by individual-level racism and xenophobia from the time they arrived in America in the late 1700s up until the present day. At the institutional level, the state has often implicitly reinforced, encouraged, and perpetuated this violence through bigoted rhetoric and exclusionary policies. COVID-19 has enabled the spread of racism and created national insecurity, fear of foreigners, and general xenophobia, which may be related to the increase in anti-Asian hate crimes during the pandemic. We examine how these crimes – situated in historically entrenched and intersecting individual-level and institutional-level racism and xenophobia – have operated to “other” Asian Americans and reproduce inequality.

W. Peters, A. Jacobson, C. Sweeney et al.

G. Elder, M. Johnson, Robert Crosnoe

E. Delong

M. Patti, A. Butte, Sarah Crunkhorn et al.

P. Kivisto, C. Lincoln, L. Mamiya

W. Murphy, E. Eizirik, S. O'Brien et al.

Carol E. Hoffecker, K. Jackson

J. Banks, C. Banks

T. Skocpol

Steven G. Brint, Jerome Karabel

M. Emerson, D. Conley

A. Smedley

Jeff Chang

Yuchang Jiang, Anton Raichuk, Xiaoye Tong et al.

Monitoring tree crop expansion is vital for zero-deforestation policies like the European Union's Regulation on Deforestation-free Products (EUDR). However, these efforts are hindered by a lack of highresolution data distinguishing diverse agricultural systems from forests. Here, we present the first 10m-resolution tree crop map for South America, generated using a multi-modal, spatio-temporal deep learning model trained on Sentinel-1 and Sentinel-2 satellite imagery time series. The map identifies approximately 11 million hectares of tree crops, 23% of which is linked to 2000-2020 forest cover loss. Critically, our analysis reveals that existing regulatory maps supporting the EUDR often classify established agriculture, particularly smallholder agroforestry, as "forest". This discrepancy risks false deforestation alerts and unfair penalties for small-scale farmers. Our work mitigates this risk by providing a high-resolution baseline, supporting conservation policies that are effective, inclusive, and equitable.

Andrea Cremaschi, Dae-Jin Lee, Manuele Leonelli

As artificial intelligence and robotics increasingly reshape the global labor market, understanding public perceptions of these technologies becomes critical. We examine how these perceptions have evolved across Latin America, using survey data from the 2017, 2018, 2020, and 2023 waves of the Latinobarómetro. Drawing on responses from over 48,000 individuals across 16 countries, we analyze fear of job loss due to artificial intelligence and robotics. Using statistical modeling and latent class analysis, we identify key structural and ideological predictors of concern, with education level and political orientation emerging as the most consistent drivers. Our findings reveal substantial temporal and cross-country variation, with a notable peak in fear during 2018 and distinct attitudinal profiles emerging from latent segmentation. These results offer new insights into the social and structural dimensions of AI anxiety in emerging economies and contribute to a broader understanding of public attitudes toward automation beyond the Global North.

D. Graeber

Luis Bértola, J. Ocampo