Does reconciliation affect your bottom dollar? The business case for honoring Indigenous rights in Canada
Bibliographic record
Abstract
Purpose In acknowledgment of the Truth and Reconciliation Commission of Canada's Call to Action #92, the purpose of this paper is to present the business case for honoring Indigenous rights in Canada. We outline the strengths as well as risk-mitigation that come from honoring Indigenous rights and present opportunities to action economic reconciliation. Design/methodology/approach The authors utilize professional insights, lived community experience and research on the extent of Indigenous rights in Canada to form the business case. Findings There is evidence of risk to businesses that forgo honoring Indigenous rights. Social implications Many businesses consider Indigenous rights and relationship building as barriers to moving forward on projects such as economic development. Through a rights-based lens, this paper outlines that honoring Indigenous rights is a business opportunity producing risk mitigation and social value. Originality/value The paper offers a simplified and concise business case to a complex issue and suggests an approach honoring Indigenous rights for non-Indigenous businesses.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.058 | 0.025 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".