Rethinking Global Citizenship Resources For New Teachers: Promoting Critical Thinking and Equity
Bibliographic record
Abstract
Global citizenship education, or education aiming to develop teacher candidates' knowledge and empathy with transnational challenges, has become increasingly recognized as an important field internationally, requiring a particular set of pedagogical understandings and tools to facilitate learning.Traditionally, global citizenship education resources have been developed by non-governmental organizations to aid teachers in classroom presentations and to profile issues of concern to their constituencies.Understandably, some of these resources require revisions to correspond with teacher candidates' grade levels, learning styles, subject-based disciplines and broad issues of equity.Accordingly, we developed a guide for teacher education candidates and novice teachers based on a collaborative inquiry model that we called a "Primer" in order to assess the compatibility, equity and adaptability of classroom-ready global citizenship education materials.Our aims were to understand how pre-service candidates made use of the Primer as a means to integrate global citizenship topics in the regular curriculum.Based on our research-which was informed by a mixed-method methodology consisting of focus groups, journal reporting, and survey data-we documented teacher education candidates' experiences with the Primer.Our research of how teacher candidates made use of the Primer, offers evidence that their desires and abilities to teach global citizenship themes through classroom-ready resources has been facilitated by utilizing the Primer.* If religion is at the root of a culture's identity, is there sufficient space devoted to defining religious principles and their relationship to culture?* Does the material cover the economic, colonial or political basis of this culture?* Are diverse family/living arrangements such as same sex partners, single parents or grandparents represented in the resource?* Does the resource feature people with dis/abilities?Could you integrate questions of ableness with this resource?* Within the resource, is there evidence of differing class-based families/communities?
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".