Karen Martin and Dane Malenfant have been named Rathlyn Fellowship recipients for the 2023-24 year. This fellowship of $12,500 is awarded yearly by the Indigenous Studies Program to support Indigenous graduate students in their pursuit of excellence in research.
Revitalizing theĀ Miāgmaw language
Karen Martin, a Miāgmaw student from Listuguj, is in her second year of a masterās degree in the program of Education and Society. Martinās thesis aims to create a Miāgmaw Verb Conjugation Tool to support language revitalization efforts in Listuguj. Ā Focusing on intransitive verbs, commonly used in early-level language learning, the project will identify and document these verbs in past, present, and future tense.
By consulting with expert language speakers, and elders, Martinās project will establish a database format reference tool that can aid in curriculum development and resource creation for Miāgmaw language education, beginning with the conjugation of one verb and will gradually expand to others. The project emphasizes ethical considerations, including informed consent and fair compensation for participants. Ultimately, this tool will contribute to the broader goal of revitalizing the Miāgmaw language by providing educators with accessible resources for language instruction.
Martin, who started learning her language at the age of eight, has experienced the challenges of cultural disconnection herself and recognizes the transformative power of language in shaping oneās worldview. āLanguage was the most transformational in terms of changing my ways of thinking and seeing the world,ā she says.
Call to all Canadians for support
Martin has been teaching her language to youth in her community since 2019. The ongoing support of her childhood language teachers helps her recreate the same kinds of rich relationships with her students today and is ensuring that future generations embrace their culture with pride.Ā She says students often tell her they will also become teach in Miāgmaw one day. Ā āI believe it is now that we lay the seeds, the tools, and the love for our languages to ensure all of our languages survive,ā she says.
Looking to the future, Martin is hopeful. Ā āI see a bright future for Miāgmaw immersion,ā she says.
But Martin says that the responsibility for language revitalization extends beyond Indigenous communities. She calls upon all Canadians to recognize the value of linguistic diversity and to actively support efforts to preserve and promote Indigenous languages. āIt will take every single Canadian to support and make space for languages on their territories,ā she says.
āWelaālieg Gisulgw ugjit tliāsuti, taān teloltiāgw, ugsātqamu aqq taān teliangweiwiāeg āmsāt,ā she says. āThank you, Creator, for the language, our culture, the earth and taking care of us all.ā
Challenging AI algorithms
Dane Malenfant,Ā aĀ citizen of MĆ©tis Nation Saskatchewan, is finishing the first year of aĀ masterās degree in Computer Science.
Malenfantās thesis focuses on the principles of reciprocity ā a fundamental concept deeply ingrainedĀ inĀ traditionalĀ Plains IndigenousĀ ways of life. Malenfant is investigating whether this is a learnable concept in current artificial intelligence (AI) systems.
Reciprocity, as Malenfant explains, is more than just a notion. āItās a way of being ā a tradition rooted in giving and receiving,Ā equilibriumĀ with the naturalĀ processes of theĀ world,ā he says.
Drawing from his experiences growing up in Saskatchewan andĀ understandingĀ MĆ©tis and otherĀ Plains IndigenousĀ histories and culture, Malenfant wants to challenge AI algorithms to understand andĀ embedĀ these teachings.
Reciprocity and cooperation
The Manitokanac which means āthe great spirit,ā are wooden shrines set upĀ in areas, like travel routes, byĀ Plains Indigenous peoples, offering tools, food, and medicine for travelers. These shrines areĀ physical images ofĀ reciprocity, where one takes only what is needed and gives back what is no longer required ā a practiceĀ traditionally emphasized in MĆ©tis and otherĀ Plains IndigenousĀ values.
His research project challenges the current state-of-the-art AI systems byĀ testingĀ the concept ofĀ traditionalĀ reciprocity into reinforcement learning tasksĀ as an extension of previous machine learning work on reciprocity and cooperation. Specifically, the project utilizes a novelĀ redesign of theĀ classic credit assignment problems, where AI agentsĀ must navigate and decide the importance of actions and places at different times. Future work will explore the use ofĀ more advanced decision-making algorithmsĀ and more complex environments to further investigate the emergence ofĀ traditionalĀ reciprocityĀ behaviourĀ in AI systems.
Through research like his, Malenfant envisions aĀ collaborativeĀ future whereĀ traditional Indigenous science and knowledge are represented,Ā andĀ the development of AI will improve language acquisition and economic opportunities for Indigenous nations.
