Research is an offering: decolonizing interior spaces for indigenous belonging in academia
Bibliographic record
Abstract
This project used interior design to reimagine an academic research space as a place that encourages Indigenous research practices and fosters belonging. Post-secondary education is essential to the continuation of countless disciplines and the betterment of Canadian people. However, in its current Western state, the Canadian post-secondary system is not in a place that properly accommodates the Indigenous student population. Historically, it has received an inequitable, much less an enthusiastic promoter of Indigenous research and academia. Modern institutions do not possess the infrastructure for encouraging knowledge keeping or extensive cultural integration, nor the interest in preserving Indigenous language, history or culture, which can negatively affect the work and lives of First Nations, Métis and Inuit scholars. Academic spaces designed specifically for Indigenous students and professionals and their particular research methodologies and knowledge types have become a typology of recent importance. The concern comes from increased interest among Indigenous students and added support of Indigenous peoples to pursue post-secondary education by Indigenous governments, the federal government, and other advocate organizations. While many institutions have a relatively insignificant discourse on what constitutes Indigenous physical space in academic environments, there exist positive opportunities for revaluating the roles of Indigenous students and researchers in physical, academic environments. This project explored Indigenous placemaking to derive a unique typology and set of spaces that will take up space in the current academic research model and strengthen Indigenous roots in Canadian academia. This project had two objectives: one, to create a concrete, dedicated space for the creation and circulation of Indigenous knowledge for application in both academic research and community efforts, and two, to understand how a sense of “place” for Indigenous students is able to be improved upon using interior design within an academic, physical space. The result is Mâtinawewin (Cree, “the act of making an offering”), a collaborative, holistic, community-focused research centre that embodies its name.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.021 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".