Science Fiction, Radical Democracy, and World Building: A Pedagogy of Unknowable Futures
Bibliographic record
Abstract
The unknowability of the future implicates everyone, yet the narratives of mastery which shape pedagogical approaches to the future do not allow students the opportunity to explore the uncertainty that comes from ultimately unknowable futures. This dissertation therefore foregrounds the exploration of uncertainty by envisioning science fictional, collaborative world building as a space in which students can imagine contested views of the future that move beyond predicting future problems. This study occurred in two stages: first, a reflexive ethnography framed within participatory action research in one secondary-level English classroom over three months, which involved exploring science fiction (SF) with students who then mobilized science fictional storytelling to collaboratively imagine the future of Toronto; and second, a world building assignment that was designed and informed by findings from stage one and used with pre-service teachers in order to facilitate speculative pedagogical explorations as they imagined myriad potential futures of society and schooling through SF. In stage one, various qualitative methods were used to explore students engagement with SF, the future, and storytelling, including observations and fieldnotes, a questionnaire on students thoughts on the future, semi-structured group interviews, in-class discussions, and contributions to the collaborative world building project. Data is analyzed through thematic analysis, discourse analysis, and critical theories to gain a deeper understanding of issues of representation, power, and intersectionality in students engagement with one another throughout the project, in pursuit of understanding how students envisioned a collective, contested future together. In stage two, pre-service teachers world building work is analyzed through thematic analysis, with particular attention to the development of speculative pedagogies which centre futures that are open and uncertain. Informed by thinking on radically democratic pedagogy, poststructuralism, and critical theory, in addition to genre studies within SF scholarship, this study contributes to a reframing of the future within education by moving away from the goal of mastering unknowable futures, and instead towards engaging in a collectively constructed exploration of uncertainty, and further positions SF as a promising and largely untapped resource integral to narratively navigating challenge and change.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.048 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".