Contested Modernities: Decolonial Knowledges, Transamerican Perspectives

Latin American Studie

An Unexpected Influence

Notes and handouts from an informal presentation at the John Carter Brown Library

Women, Men, and the Legal Languages of Mining in the Colonial Andes

Histories of colonial Latin American mining have cemented the image of a scientifically backward society whose pursuit of easy wealth sacrificed the lives of indigenous and African miners in places like Potosí. By examining a mid seventeenth-century mine dispute between an Andean woman and a Spanish man, this article suggests how legal archives can reveal indigenous women’s contributions to the history of colonial silver. It also provides an appendix with one hundred cases of indigenous, creole, and Spanish women miners, refiners, and managers in Alto Perú, 1559–1801, suggesting how women of different socioeconomic and technical backgrounds participated in the silver industry

Actividades latinoamericanas en el espacio ultraterrestre en el siglo XXI: una actualización

En el siglo XXI, los países latinoamericanos han hecho esfuerzos significativos para avanzar en sus programas espaciales. Estos esfuerzos han abarcado desde una indagatoria sobre la instalación de un sistema de satélites, como es el caso en Colombia, hasta el lanzamiento de satélites con la ayuda de gobiernos extranjeros, en el caso de Brasil, Argentina y Bolivia. En todos estos casos, la falta de un marco jurídico coherente que apoye un programa espacial sólido que proporcione comunicaciones por satélite a las poblaciones más vulnerables es uno de los desafíos más apremiantes. El Consejo Asesor de Generación Espacial (SGAC) podría resolver este problema mediante un proyecto unificador que pondrá todas las mentes y desarrolladores en el objetivo común de alcanzar la autonomía espacial para América Latina.In the twenty-first century, Latin American countries have made significant efforts to advance their space programs. These efforts have ranged from inquiring about setup of a satellite system, as is the case in Colombia, to launching satellites with the aid of foreign governments, in the case of Brazil, Argentina and Bolivia. In all these cases, the lack of a coherent legal framework that supports a solid space program that provides satellite communications to the most vulnerable populations is one of the most pressing challenges. The Space Generation Advisory Council (SGAC) could solve this problem in the form of a unifying project that will put all minds and developers to work towards the common goal of achieving space autonomy for Latin America

Literacy and educational fundamentalism: an interview with Allan Luke

An interview on literacy at McGill University, 2003

AmericasNLI: Machine translation and natural language inference systems for Indigenous languages of the Americas

Little attention has been paid to the development of human language technology for truly low-resource languages—i.e., languages with limited amounts of digitally available text data, such as Indigenous languages. However, it has been shown that pretrained multilingual models are able to perform crosslingual transfer in a zero-shot setting even for low-resource languages which are unseen during pretraining. Yet, prior work evaluating performance on unseen languages has largely been limited to shallow token-level tasks. It remains unclear if zero-shot learning of deeper semantic tasks is possible for unseen languages. To explore this question, we present AmericasNLI, a natural language inference dataset covering 10 Indigenous languages of the Americas. We conduct experiments with pretrained models, exploring zero-shot learning in combination with model adaptation. Furthermore, as AmericasNLI is a multiway parallel dataset, we use it to benchmark the performance of different machine translation models for those languages. Finally, using a standard transformer model, we explore translation-based approaches for natural language inference. We find that the zero-shot performance of pretrained models without adaptation is poor for all languages in AmericasNLI, but model adaptation via continued pretraining results in improvements. All machine translation models are rather weak, but, surprisingly, translation-based approaches to natural language inference outperform all other models on that task

Grantmaker's Guide: Strengthening International Indigenous Philanthropy

As members of International Funders for Indigenous Peoples (IFIP), we are anxious to grow the field and bring an infusion of new faces, sources of investment and expertise, along with the professional camaraderie that grows from shared commitment and passion. IFIP is an affinity group of the Council on Foundations dedicated to assembling international grantmakers in support of Indigenous philanthropies and fostering funding partnerships to improve the lives of Indigenous People globally. Over the past decade, IFIP has convened conferences and workshops that catalyze thoughtful, engaged collaboration among participants.Experienced donors recognize the resilience of Indigenous Peoples, often in the face of overwhelming odds and continual attacks on many fronts. Their diversity and creativity is an essential resource for the future of our planet. There is important work of global significance underway. Nevertheless, there are technical challenges that this guide can help identify and overcome. Many standard practices simply won't work. We need to be on the ground listening to people and stretching our imaginations. We cannot wait for the 'experts' to send us polished proposals that meet our criteria and timetables. Truly effective philanthropy has always relied on ingenuity and creative paths of understanding to effect deep change in the world.We can embrace and drive this change. This guide describes the practical experiences of those pioneers who have forged ahead

Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-Mixtec

In this paper, we present a parallel Spanish-Mazatec and Spanish-Mixtec corpus for machine translation (MT) tasks, where Mazatec and Mixtec are two indigenous Mexican languages. We evaluated the usability of the collected corpus using three different approaches: transformer, transfer learning, and fine-tuning pre-trained multilingual MT models. Fine-tuning the Facebook M2M100-48 model outperformed the other approaches, with BLEU scores of 12.09 and 22.25 for Mazatec-Spanish and Spanish-Mazatec translations, respectively, and 16.75 and 22.15 for Mixtec-Spanish and Spanish-Mixtec translations, respectively. The findings show that the dataset size (9,799 sentences in Mazatec and 13,235 sentences in Mixtec) affects translation performance and that indigenous languages work better when used as target languages. The findings emphasize the importance of creating parallel corpora for indigenous languages and fine-tuning models for low-resource translation tasks. Future research will investigate zero-shot and few-shot learning approaches to further improve translation performance in low-resource settings. The dataset and scripts are available at \url{https://github.com/atnafuatx/Machine-Translation-Resources}Comment: Accepted to Third Workshop on NLP for Indigenous Languages of the America