Ethnocultural diversity, Indigeneity, and intercultural understanding in the context of planning for reconciliation: Perspectives from the City of Winnipeg, Manitoba
Bibliographic record
Abstract
Through a case study of the city of Winnipeg, this paper examines perspectives on Indigeneity and ethnocultural diversity in the context of planning for reconciliation at the scale of a city as inhabited by both Indigenous and racialized communities. The authors reveal a separation between Indigeneity and immigration discourses in academic literature and in planning practice and problematize the processes by which cities plan for diversity. This paper draws from 42 semi-structured interviews conducted with Indigenous and racialized inhabitants, organizational officials, and planners in Winnipeg to reveal that amid the absence of strong municipal planning and programming, intercultural understanding between Indigenous and immigrant inhabitants has developed in the city, and that planners can do more to help to sustain and enhance it. The authors conclude that by increasing the level of literacy and competency in ethnocultural diversity and in Indigeneity, and by focusing on processes of planning, planners and municipal officials can play a more constructive role in enhancing intercultural relations and advancing reconciliation in Winnipeg and other Canadian cities.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".