Reflections on Lessons Learned: A Journey of Discovery
Bibliographic record
Abstract
Attending the Interdisciplinary Dialogue on the Global Refugee Crisis in relation to our Bachelor of Social Work course on Intercultural Practice started us on our journey of discovery and learning. It brought the headline news of refugees, settlement, and crisis to our door steps. It changed us from observers to participants in trying to understand the issue and finding solutions. We wanted to learn more and explore further. In this presentation, we wanted to share our journey of discovery from why we participated in the forums and what we learned about the Global Refugee Crisis to how we viewed things as social work students. We hoped to link the lessons we learned to our personal lives and academic lives as well as to our ongoing growing professional identity. Our goal is to continue the dialogue on Global Refugee Crisis, by putting ourselves in the role of active actors of social change. As future social workers and as responsible members of humanity, we will endeavor to continue to learn, reflect and above all to be agents of change to make this world a place where the well-beings and dignity of everyone is ensured. Discipline: Social Work Faculty mentor: Dr. Valerie Ouedraogo
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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 | 0.033 | 0.112 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.029 |
| Scholarly communication | 0.023 | 0.023 |
| Open science | 0.006 | 0.023 |
| Research integrity | 0.010 | 0.038 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".