The Wakanda Workshop: A graduate student organized session - Building Wakanda: Graduate students envision the Africa that they want
Bibliographic record
Abstract
The Wakanda Workshop: a graduate student organized session\nBuilding Wakanda: Graduate students envision the Africa that they want\nRationale: This session is a workshop facilitated by two graduate students who will guide their peers through two rounds of breakout group discussions. The first round is about the opportunities available for graduate students to reframe the knowledge about Africa away from the dominant deficit-model. The second round focuses on potential strategies to further mobilize the knowledge produced in service of the African continent. Each discussion group will have a rapporteur who, at the end of the session, will assist the main facilitators to produce a short report that participants will take back to their home institutions. The intent is that the grad students feed the session report into road maps of activities in their home institutions.\nFacilitators:\nCarla Jobert: Carla Joubert is an Associate Lecturer at the University of Wisconsin-La Crosse. She is a Doctoral Candidate in History; her dissertation focuses on the role of white women in the settler colonisation of the Zuid-Afrikaansche Republiek and Alberta, Canada in the mid-nineteenth century.\nCarelle Mang-Benza: Carelle is a third-year PhD candidate in Geography and Environment at Western University. Her research focuses on the current low-carbon energy transition and relationships between Indigenous and non-Indigenous peoples.\n*Please note this session will be recorded and posted on this page after the conference.\nMeeting ID: 921 8023 8171
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.132 | 0.042 |
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".