Global challenges in securing equity and human rights: Re-envisioning the role for evaluation in the contemporary HIV/AIDS epidemic
Bibliographic record
Abstract
Kia ora. It is an honour to join you in this important discussion of evaluation's role and contribution to creating equitable societies. I am speaking to you from my current hometown of Okemos, Michigan, in the United States (US) rather than, as I had hoped, in a conference meeting room in Rotorua. Okemos is rightfully Ojibwe tribal land. Chief Okemos, after whom the town is named, was the Ojibwe chief who represented his people when they, along with the Ottawa and Potawatomi, were forced to yield their territory to the US government in the 1819 Treaty of Saginaw. Michigan State University also sits on the forcibly surrendered lands of the Three Fires Confederacy.
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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 | 0.119 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.092 |
| Scholarly communication | 0.033 | 0.036 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.018 | 0.027 |
| Insufficient payload (model declined to judge) | 0.005 | 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".