Bibliographic record
Abstract
Higher education is tasked with preparing students for a culturally diverse and globalizing world. Additionally, western nations have an increasingly diverse student population and know the success of their students will depend in part on being able to navigate diversity. There is therefore good reason for institutions of higher learning to promote and facilitate the development of ‘global citizens’ – people who can work and relate across borders and boundaries, both real and perceived. However, teachers are not necessarily equipped to foster this learning. Many teachers are used to a reproductive way of teaching while the learning that is needed here is identity learning, directed at dialogue, internally as well as externally. This chapter proposes the potential of creative, expressive and reflective writing as a way in which personal development – a form of a reflexive internal dialogue – can be fostered to promote cultural healing and global citizenship. The writing method will be described and a case study on cultural healing in the context of Canada’s reconciliation efforts with Aboriginal people will be used to illustrate the learning process involved. The processes of writing the self and re-narrating identity has several promising benefits for both students and teachers in higher education. First it allows us to learn more about ourselves and what blocks our learning (i.e. promotes self-reflection). Second, it allows us to change our story and our identifications and therefore choose differently (i.e. self-direction). Third, it is a companion on the road of life where we literally learn to talk and listen to ourselves and articulate the tacit knowledge that can be unearthed through narrative, journal, and poetic writing. Fourth, the method is playful and creative and although tears are frequently shed in the process, students report a great enjoyment in writing and sharing their stories with others. It is a meaningful dialogue about experience and also has the potential of promoting cultural (Lengelle, Jardine, & Bonnar, 2018) healing in the context of a very diverse student body (Banks, 2015). It also has the potential for creating new bonds in the classroom and allows teachers in higher education to engage in the difficult work of facilitating global citizenship learning. The internal dialogue described here also allows us to ‘clean up’ judgements and become aware of the need to reach out to others. Not only the actual sharing of vulnerable writing in a class or online setting shows us we are not alone, but ‘writing the self’ focuses deliberately on where we have become fearful about our own and others’ identities and allows us a learning process to unearth those things, heal them in order to reach out to others.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.038 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".