Sustainable Operations through Collaborative Initiatives with Local Indigenous Communities: Case Studies in North America
Bibliographic record
Abstract
Abstract A global energy technology company has empowered its local teams to prioritize environmental and social initiatives that bring the most benefit to local stakeholders. This paper describes case studies from North American collaborative initiatives with Indigenous communities to encourage participation in the workforce and develop inclusive environmental, sustainability, and educational programs. Strengthening collaborative relationships with Indigenous communities has increased employment and opened business development opportunities for those communities, provided a more culturally diverse workforce for the energy technology company, and assisted the community in achieving their priorities using digital technology. The global energy technology company's local teams set objectives and developed programs with local Indigenous communities. In the United States, a customized training and workforce development program was created to provide local candidates with firsthand experience of working on the Alaska North Slope. In Canada, business development opportunities and Indigenous needs were analyzed to create unique business synergies. An environmental recycling project in Canada has provided business development opportunities to a local area Indigenous community. Rubber components that were once sent to landfills are now donated to an Indigenous-owned business to be recycled into new rubber industrial items to be sold locally. Another initiative described in the paper focuses on finding a solution for a community's inability to consistently access clean water and used digital technology to solve water imbalance issues in the community's water treatment plant. The energy technology company provided educational scholarships for the community's water treatment plant employees, in addition to software licenses and training to use company process simulation software and 3D modeling technology. This collaborative effort has helped the community achieve its priority to obtain consistent access to clean drinking water through its water treatment facility. The initiative has been presented at local water conferences.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".