Decolonial affordances of a communal heritage platform: A case study of the Reciprocal Research Network
Bibliographic record
Abstract
Museums are increasingly reckoning with their roles in the colonization of Indigenous peoples as they seek to engage diverse forms of participation and justify their social relevance. Many are turning to digital solutions to aid with these endeavors, including digital repatriation/return platforms. How users interact with these platforms to create knowledge and how these platforms contribute to a larger decolonial aspiration is not well understood. In this study, I explore these issues, drawing on postcolonial/decolonial theories and affordance theory, using the Reciprocal Research Network (RRN). The RRN was co-designed by the Museum of Anthropology, U’mista Cultural Society, Musqueam Indian Band, and Stó:lō Nation/Tribal Council to meet the need for museums to involve Indigenous communities in heritage work. With an actor-network theory approach, I interviewed nine stakeholders (users, developers, and steering group members) of the RRN and explored the platform and documents to identify RRN actors’ specific enactments of decolonial aspirations as affordances. My exploration revealed that the RRN is bound as a network by the Item Search, which allowed for multiple entry points into a vast collection of heritage objects. These multiple entryways broke down technical and cultural barriers to and allowed for plurality in interaction with heritage. The RRN also allowed a direct contestation of museums’ data ownership by allowing users to dictate how shared knowledge is used. The RRN also was deeply embedded in Vancouver, BC, and its surrounding area, where multiple points of offline/online interaction allowed for deep explorations of the histories of First Nations peoples and aided in projects aimed at their revival. However, platform logics and museums’ lack of participation in relationship-building threatened the decolonial aspirations of the RRN. Broadly, my findings indicate that the RRN, as a communal heritage platform, is a necessary step towards building relations with Indigenous communities that requires further participation on museums’ part to develop.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.000 |
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 teacher head, 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".