Reframing Metanarratives on Africa and the Caribbean Through Decolonial Pedagogy: Duoethnography as Embodied Methodology
Bibliographic record
Abstract
This paper presents the experiences of two educators in the African diaspora in the post-secondary education landscape of Canada who engage in the challenging work of deconstructing colonialism and neo-colonialism within the classroom communities as it concerns students from Continental Africa and the English-speaking Caribbean. This paper employs a duoethnographic methodological framework which is a collaborative research methodology that invites two or more researchers to serve as sites of inquiry. The methodology is utilized as a dialogic process that draws attention to the role of emotional and bodily knowledge in teaching, learning and research processes. This paper also draws on Pohlhaus Jr.’s (2012) insights on dialectical relations of situatedness and interdependence and how their application can influence subjectivity and interpretations of lived experience in a manner that describes how educators can use epistemic resources to unsettle metanarratives of incongruence between ways of knowing among African Continental Peoples and Diasporic Africans. To operationalize decolonial pedagogy, Critical Discourse Analysis (CDA) is employed as a mode of teaching and learning using resources such as concepts, language, text and strategies to support the active engagement in the processes of deconstruction, construction and reconstruction of racial discourses that are abound within Canada’s multicultural milieu.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.044 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".