Hasil untuk "Anthropology"

M. Strathern

In the most original and ambitious synthesis yet undertaken in Melanesian scholarship, Marilyn Strathern argues that gender relations have been a particular casualty of unexamined assumptions held by Western anthropologists and feminist scholars alike. The book treats with equal seriousness - and with equal good humor - the insights of Western social science, feminist politics, and ethnographic reporting, in order to rethink the representation of Melanesian social and cultural life. This makes "The Gender of the Gift" one of the most sustained critiques of cross-cultural comparison that anthropology has seen, and one of its most spirited vindications.

R. Benedict

For more than a generation, this pioneering book has been an indispensable introduction to the field of anthropology. Here, in her study of three sharply contrasting cultures, Benedict puts forward her famous thesis that a people's culture is an integrated whole, a personality writ large. Includes

H. Markus, S. Kitayama

J. Haidt

A. Appadurai

B. Latour

C. Geertz

Douglas Harper

M. Hauser, Noam Chomsky, W. Fitch

M. Sheller, J. Urry

A. Escobar

M. Lamont, Virág Molnár

I. Hacking

Dipesh Singh Chuphal, Vimal Mishra

Abstract Reliable streamflow projections are essential for effective water‐resource management and climate adaptation. However, streamflow projections are associated with large uncertainties due to divergent precipitation projections from climate models, which directly propagate into hydrological estimates. Observation‐constrained approaches that condition future projections on past observations have been shown to reduce such uncertainties; however, they have not been applied to streamflow projections across the Indian rivers. Using long‐term streamflow and global mean surface temperature observations, climate model projections, hydrological modeling, and a Bayesian detection–attribution framework, we developed observational constrained streamflow projections for nine major Indian rivers. The method reduces the 5–95% confidence interval of future streamflow projections by nearly one‐third compared to raw multimodel ensembles, with constraint strength controlled by internal streamflow variability and inter‐model spread in the unconstrained ensemble. Projection uncertainty is further reduced to ∼20% when considering projections based only on skillful climate models. Constrained projections indicate significant increases in streamflow in the near‐, mid‐, and far‐future periods, except for the Cauvery basin, which shows a near‐term decline. Applying the method to raw precipitation projections reveals comparable constraint strength and increases confidence in the results, given the strong dependence of Indian river flows on precipitation. Our findings underscore the importance of combining skillful climate models with post‐processing constraint methods to substantially reduce model‐based uncertainty. Overall, our results provide critical insights into future streamflow changes across Indian rivers, supporting long‐term water‐resource planning and climate‐resilient management.

Sangmitra Madhusudan, Trush Shashank More, Steph Buongiorno et al.

Existing cultural commonsense benchmarks treat nations as monolithic, assuming uniform practices within national boundaries. But does cultural commonsense hold uniformly within a nation, or does it vary at the sub-national level? We introduce Indica, the first benchmark designed to test LLMs' ability to address this question, focusing on India - a nation of 28 states, 8 union territories, and 22 official languages. We collect human-annotated answers from five Indian regions (North, South, East, West, and Central) across 515 questions spanning 8 domains of everyday life, yielding 1,630 region-specific question-answer pairs. Strikingly, only 39.4% of questions elicit agreement across all five regions, demonstrating that cultural commonsense in India is predominantly regional, not national. We evaluate eight state-of-the-art LLMs and find two critical gaps: models achieve only 13.4%-20.9% accuracy on region-specific questions, and they exhibit geographic bias, over-selecting Central and North India as the "default" (selected 30-40% more often than expected) while under-representing East and West. Beyond India, our methodology provides a generalizable framework for evaluating cultural commonsense in any culturally heterogeneous nation, from question design grounded in anthropological taxonomy, to regional data collection, to bias measurement.

Jiaquan Wan, Junchao Wang, Wei Zhang et al.

Study region: The Three Gorges Reservoir Area (TGRA) Study focus: TGRA faces increasing vulnerability to extreme precipitation events driven by complex convective weather systems. Radar echo extrapolation—predicting future precipitation patterns from current radar data—is essential for early warning systems but faces significant challenges in this topographically complex region. While data-driven approaches have advanced the field, current convolutional neural network-based diffusion models struggle with the TGRA's dynamic meteorological conditions due to their reliance on translational invariance, which often fails to capture rapid weather transitions in complex terrain. New hydrogeological insights from the region: To address these limitations, we introduce RadarDiT, a Vision Transformer-based diffusion model specifically engineered for radar extrapolation in the TGRA. First, we develop a five-year radar dataset capturing diverse convective weather phenomena unique to this region. Then, leveraging this dataset, RadarDiT employs multi-layer Vision Transformers that effectively model global dependencies and complex spatial relationships, enabling accurate prediction of convective cell evolution. Our model demonstrates superior performance in maintaining strong echo and spatial coherence over longer forecast horizons. Quantitative evaluations across multiple metrics and thresholds confirm RadarDiT's enhanced skill in forecasting heavy precipitation events, with particular improvements in Critical Success Index at higher radar echo values. This work establishes a foundation for more reliable nowcasting systems in regions with complex terrain and dynamic weather patterns, directly supporting enhanced disaster preparedness and response strategies.

Qiying Yu, Wenzhong Li, Yungang Bai et al.

Study Area: The Tailan River Basin in the Aksu region and the Yulong Kashi River in the Hotan River Basin of Xinjiang are located at respective geographical coordinates of 80°21'44'' to 81°10'14'' E, 40°41'41'' to 42°15'13'' N, and 77.25° to 81.75° E, 34.75° to 36.25° N. Study Focus: To tackle the complexity of runoff prediction in high-altitude cold regions, alongside the limitations of existing machine learning approaches, where nonlinear relationships, long-term dependencies, and sparse observational data pose significant challenges, previous models have consistently struggled to account for these issues. In response, we propose a hybrid runoff prediction model that combines Dung Beetle Optimization (DBO)'s optimization capabilities, Temporal Convolutional Networks (TCN)’s proficiency in extracting local temporal features, and the Transformer’s ability to capture long-term dependencies. In addition, the Bootstrap method is employed to merge point prediction outcomes for interval runoff forecasting, providing robust uncertainty estimates to address data limitations in these regions. New Hydrological Insights for the Region: The DBO-TCN-Transformer model consistently attains a Nash-Sutcliffe Efficiency (NSE) above 0.81, showcasing enhanced performance over traditional models. Across various forecast periods, the model’s NSE values are 6.9–26.9 % higher than those of the TCN and Transformer models, offering more reliable short-term and long-term predictions. Furthermore, the Bootstrap algorithm’s probabilistic approach provides valuable insights into forecast uncertainty, a crucial feature for managing water resources and mitigating flood risks in high-altitude cold regions with complex hydrological dynamics.

Tomer Jordi Chaffer, Dontrail Cotlage, Justin Goldston

The convergence of humans and artificial intelligence systems introduces new dynamics into the cultural and intellectual landscape. Complementing emerging cultural evolution concepts such as machine culture, AI agents represent a significant techno-sociological development, particularly within the anthropological study of Web3 as a community focused on decentralization through blockchain. Despite their growing presence, the cultural significance of AI agents remains largely unexplored in academic literature. Toward this end, we conceived hybrid netnography, a novel interdisciplinary approach that examines the cultural and intellectual dynamics within digital ecosystems by analyzing the interactions and contributions of both human and AI agents as co-participants in shaping narratives, ideas, and cultural artifacts. We argue that, within the Web3 community on the social media platform X, these agents challenge traditional notions of participation and influence in public discourse, creating a hybrid marketplace of ideas, a conceptual space where human and AI generated ideas coexist and compete for attention. We examine the current state of AI agents in idea generation, propagation, and engagement, positioning their role as cultural agents through the lens of memetics and encouraging further inquiry into their cultural and societal impact. Additionally, we address the implications of this paradigm for privacy, intellectual property, and governance, highlighting the societal and legal challenges of integrating AI agents into the hybrid marketplace of ideas.

Ooha Lakkadi Reddy

This thesis employs a hybrid CNN-Transformer architecture, alongside a detailed anthropological framework, to investigate potential historical connections between the visual morphology of the Indus Valley script and pictographic systems of the Tibetan-Yi Corridor. Through an ensemble methodology of three target scripts across 15 independently trained models, we demonstrate that Tibetan-Yi Corridor scripts exhibit approximately six-fold higher visual similarity to the Indus script (0.635) than to the Bronze Age Proto-Cuneiform (0.102) or Proto-Elamite (0.078). Contrary to expectations, when measured through direct script-to-script embedding comparisons, the Indus script maps closer to Tibetan-Yi Corridor scripts with a mean cosine similarity of 0.930 (CI: [0.917, 0.942]) than to contemporaneous West Asian signaries, which recorded mean similarities of 0.887 (CI: [0.863, 0.911]) and 0.855 (CI: [0.818, 0.891]). Across dimensionality reduction and clustering methods, the Indus script consistently clusters closest to Tibetan-Yi Corridor scripts. These computational findings align with observed pictorial parallels in numeral systems, gender markers, and iconographic elements. Archaeological evidence of contact networks along the ancient Shu-Shendu road, coinciding with the Indus Civilization's decline, provides a plausible transmission pathway. While alternate explanations cannot be ruled out, the specificity and consistency of similarities suggest more complex cultural transmission networks between South and East Asia than previously recognized.

Auwalu Abdullahi Umar, Muneer Ahmad, Dr M Sadik Batcha

The significance of libraries in preserving and maintaining history and traditional culture cannot be overlooked. It is from this purpose that libraries are to envisage in their programmes cultural activities which must be collected, documented and preserved for posterity. The usefulness of preserved information lies in the fact that the generation to come will be able to establish their identity. This will also assist them with a foundation to build from. This study focus on the growth and development of Library and Culture research in forms of publications reflected in Web of Science database, during the span of 2010-2019. A total 890 publications were found and the highest 124 (13.93%) publications published in 2019.The analysis maps comprehensively the parameters of total output, growth of output, authorship, institution wise and country-level collaboration patterns, major contributors (individuals, top publication sources, institutions, and countries). It exposed that the most prolific author is Lo P secured first place by contributing 4 (0.45%) publications, followed by Bressan V 3 (0.34%) publications in Library and Culture literature. Journal of Academic Librarianship produced the highest number of records 29 (3.26%) followed by Australian Library Journal having contributed 21 (2.36%).It is identified the domination of Wuhan University; School Information Management had contributed 6 (0.67%) of total research output. Authors from USA published the highest number of publications with a total of 244 (27.42%), followed by UK and Australia with 118 (13.26%) and 76 (8.54%) publications were produced respectively.