CONSTRUCTING CRITICAL CITIZENSHIP WITH YOUNG PEOPLE: ALTERNATIVE PEDAGOGIES
Bibliographic record
Abstract
The authors present theoretical and empirical arguments for adopting the United Nations Convention on the Rights of the Child (or CRC) to renew the teaching of citizenship to young students from a social justice standpoint (Giroux, 2003; Giroux & Searls-Giroux, 2004; Mitchell, 2010; Moore, 2008; Smith, 2007). The paper draws its analysis and conclusions from a descriptive, exploratory study with key participants from a 2009 rally hosted by Nobel nominee, child rights activist, and founder of Free the Children, Craig Kielburger. Four of the paper’s co-authors were senior elementary students initially chosen as interviewees for the investigation and subject to traditional research protocols for minors. During data collection, however, their status shifted reflexively to include their contributions – not as objects under study or subjects of the interviewer’s questions – but as co-constructors of new knowledge. Relative to the dominance of their teachers and other adult groups “engaging” their participation, this new status allowed a deeper exploration of the meanings they attached to active citizenship through an innovative dialogue (see Kellett & Ward, 2008; Kellett, Forrest, Dent, & Ward, 2004; also Devine, 2002). Through participatory lenses embedded within CRC principles, particularly Article 12, the analysis transcends traditional disciplinary silos to offer a critical and transdisciplinary alternative pedagogy.
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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 | 0.022 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.012 | 0.064 |
| Scholarly communication | 0.020 | 0.020 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.004 | 0.006 |
| 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".