Cultivating Ordinary Voices of Dissent: the Challenge for the Social Studies
Bibliographic record
Abstract
Two broad ideas emerge from reflections on my career in global and international education: first, that my ‘lived experience’ offers both intelligence and ignorance in terms or how I view the world; and second, that the essence of my humanity is enhanced through my identification with, and sense of responsibility for, fellow humans. The latter idea is encapsulated in the African philosophy of ubuntu. These two ideas prompt my contention that the global education movement has failed to adequately convey through its literature and practice the complexity and interrelatedness of global systems, including the inextricable connections between humans and their environments. The nature of contemporary global challenges, such as climate change, demands that we understand how global systems are intertwined and adjust our actions accordingly. The social studies need to be at the forefront of nurturing systems level thinking and innovation, particularly to counter the tendency arising from advances in information technology to develop cultures of conformity. Young people around the world have the potential to bring about system-wide change through their ordinary voices of dissent, a collective commitment to decision-making based on recognizing the needs of all humanity, rather than just assessing the benefits to individuals or nations.
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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 | 0.105 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.021 | 0.203 |
| Scholarly communication | 0.031 | 0.052 |
| Open science | 0.006 | 0.025 |
| Research integrity | 0.015 | 0.028 |
| 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".