CASE 5: A Stakeholder Analysis: Developing an Indigenous-Specific Intercultural Competency Training Module (Part A)
Bibliographic record
Abstract
The case focuses on developing an Indigenous-specific intercultural competency training module and outlines the steps needed to achieve this, with particular emphasis on the importance of conducting a stakeholder analysis and developing a stakeholder engagement plan. The protagonist of the case, Nia Singh, heads up the Intercultural Education Program at the Southwestern Ontario Intercultural Education Centre. After working at the organization as an intercultural education specialist for several years, Nia is looking to expand her project portfolio by redesigning the Intercultural Education Program’s pre-existing Indigenous intercultural competency training module. Nia determines the objective of the new training module will be to educate health care workers about the importance of intercultural competency within health care organizations. Specifically, the module will focus on Indigenous populations and will aim to improve the quality of care they receive so their long-term health outcomes ultimately improve. Nia works with her colleague, Steven Miller, to complete a stakeholder analysis and engagement plan, and they use four different steps to accomplish this: 1) brainstorming all possible stakeholders who have a vested interest in the training module; 2) prioritizing and categorizing each stakeholder as a core stakeholder, involved stakeholder, supportive stakeholder, or peripheral stakeholder; 3) determining the level of engagement required for each stakeholder; and 4) determining which engagement strategies to use for each stakeholder. After completing the stakeholder analysis and engagement plan, Nia and Steven arrange to interview the key stakeholders in order to gather additional opinions, ideas, and perspectives related to developing the training module. These stakeholders include health care workers, Indigenous community members, and other relevant informants. Once the interview process is complete, Nia and Steven develop a pilot version of the training module that is ready to be implemented on a small scale. However, Nia and Steven know they still have their work cut out for them in terms of identifying an effective implementation strategy. This case is intended to be a skills practice case with the primary objective of having students learn about conducting a stakeholder analysis and then learn about stakeholder engagement. By examining this case and completing the learning team activity, students will be able to understand the importance of stakeholder analysis and stakeholder engagement as they relate to developing an Indigenous-specific intercultural competency training module. Once students have acquired this knowledge, they will be able to apply stakeholder analyses and engagement strategies to developing a variety of public health programs. However, given that the training module focuses on Indigenous populations, the case will focus on concepts related to health equity and the barriers faced by Indigenous people when they access health care services. A secondary learning objective is for students to acquire knowledge pertaining to intercultural competency, particularly in terms of its significance within the field of public health and how it can be used as a strategy for reducing health disparities for other marginalized populations.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".