Shifting the Burden: Corporate Indigenous Relations and How They Can Go Wrong
Bibliographic record
Abstract
This paper utilizes the Shifting the Burden Archetype (Senge/Stroh) to document a systemic pattern that is unfortunately, often unconscious to the parties involved and inadvertently leads to the undermining of corporate or government/Indigenous relationships, despite best intentions. Based on over a decade of experience in these contentious contexts, the author(s), document a set of interacting feedback loops that illustrate an unfortunate set of patterns of behaviour, based on starkly different worldviews, in which the choice to engage in more superficial attempts at relationship building actually undermines the ability of the parties to engage in the more difficult but fundamental solution of trust-based relationships. Recommendations for interventions in these typical or archetypal relationships will be made based on an understanding of the dynamics of the system and process design.
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 | 0.020 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.025 | 0.109 |
| Scholarly communication | 0.025 | 0.032 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 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".