Toward the restoration of Indigenous land and life through SING - the Summer Internship for INdigenous Peoples in Genomics SING Sábme - Sámi territories
Bibliographic record
Abstract
The Arramat Global Transformation Pathway 5 (T5) Decolonizing Science and Education aims to build a network and create a space toaddress the challenges and opportunities for Indigenous-led science,technology, and society research and education. Within this framework, we aim to organize a series of webinars that willbe recorded and published as vodcasts - to highlight projects and workthat are actively promoting the decolonization of science and education. We welcome you to join our very first webinar on December 15,2025, 6-7.30 PM Central European Time. Click here for Calendarinvite to get your time. Content: We begin with an introduction of the T5, followed by apresentation about the Summer internship for INdigenous peoples inGenomics (SING) program which first started in 2011. We then present the one-week SING Sábme workshop held in August 2025, with the help of a short film. The scientists and Sámi hosts will then present their reflections and insights. Thereafter we will open the floor for an opportunity to ask questions, discuss, exchange perspectives and ideas. Translation: French and Spanish is organised. For translation into otherlanguages within Arramat, please reach out to organizers latest byDecember 7 at email: arramatpathwayt5@gmail.com Invitation: The webinar/ vodcast is open to all Arramat members andalso open to all others interested in the themes discussed. Arramat members who wish to join the webinar as panelists pleaseemail us latest by December 14 at arramatpathwayt5@gmail.com. Program Opening and Introductions A Decade-Plus of DecolonizingScience - SING- Summer Internshipfor INdigenous people in Genomics, Kim TallBear Introduction to SING Sábme, May-Britt Öhman Film SING Sábme The SING experience: Reflections and insights by scientists and Sámi hosts Q and A Panelists May-Britt Öhman, Associate professor in Environmental History,Researcher, Centre for Multidisciplinary Studies on Racism, CEMFOR, Uppsala University, T5 Co-lead, Cofounder of SING Sábme (Lule and Forest Sámi) Kim TallBear, Professor, American Indian Studies, University of Minnesota,T5 Co-lead, Co-founder of SING USA, Canada and Sábme (Sisseton-Wahpeton Oyate) Elizabeth Nelson, Assistant professor, Metagenomics Laboratory for ancient and modern DNA,Southern Methodist University, Co-founder of SING Sábme (Turtle Mountain Band ofChippewa) Warren Cardinal McTeague, Assistant professor, Canada Research Chair in Indigenous Peoples, Governance & Environmental Relations, Dept of Forest and Conservation Sciences, University of British Columbia, T5 Co-lead, Co-founder of SING Sábme (Métis and Cree of Lac La Biche and Fort McMurray ) Tina Eriksson. Reindeer herder in Gällivare Forest Sámi community, Flakaberg group,and a tradition bearer of reindeer herding knowledge. Co-founder of SING Sábme Michael Guttorm,Eriksson Årsjok, Reindeer herder in the Gällivare Forest Sámi community, Flakaberg group, a tradition bearer of reindeer herding knowledge. Co-founder of SING Sábme Henrik Andersson, Reindeer herder of the Gällivare Forest Sámi village, Flakaberg group. Activist and defender of Sámi rights. Local guide who shares his cultural knowledge with visitors and students. Co-founder of SING Sábme. Hampus Andersson, Young reindeer herder of the Gällivare Forest Sámi village,Flakaberg group. He is one of the youngest herders working to carry on his family tradition. Co-founder of SING Sábme. Elle Eriksson, Member of the Gällivare forest Sámi community, Flakaberg group and Ph.D. student in Forest Science. Co-founder of SING Sábme Batzorig Tuvshinjargal, MA student at the Sustainable Development programme, Uppsala University, and intern with CEMFOR and the Arramat T5 pathway assisted in setting up the webinar and moderated. Jacob Smallboy, MA student at UBC Faculty of Forestry & Environmental Stewardship, assisted the webinar.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".