Unpacking Self and Silence: Looking Inward, Looking Outward, Looking Through
Bibliographic record
Abstract
Looking inward as a mother, I see that autobiographical narrative inquiry has further deepened my understanding that my children’s dual identity (Muslim Canadians) is not breaking them apart, rather putting them together. Looking outward as a researcher, poetic representation has given me a voice where, instead of fearing silence, I am able to “inhabit a more ambiguous and flexible sense of self” (Boler, 1999, p. 176). I am able to act as an interpreter between the chaos of my experiences and an assembly of unbroken monologues and sporadic dialogues. Finally, looking through as an amateur poet, I practice poetry “as a method of inquiry to move into [my] own impossibility, where anything might happen—and will” (St. Pierre, 2005, p. 973). I create opportunities for meaning making and insights as my stories and poems resonate for others, and in how my stories inform, enhance, and deepen parents’ and educators’ knowledge and conceptualizations of an inclusive school community.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.052 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".