The Dreamwork of Childhood Memory: The Futures Teachers Make from the Schooling Past
Bibliographic record
Abstract
HILDHOOD MEMORIES BRING TO THE PEDAGOGICAL PRESENT traces of the past (Britzman, 2003) yet also telegraph dreams about how structures of schooling and society might be imagined otherwise.In teacher education, memories are often used in support of critical reflection.They provide the raw material for prospective teachers to contemplate both desirable and undesirable aspects of the teacher's role and to make observations about issues relating to classroom authority, values, and expectations (Chang-Kredl & Kingsley, 2014;Miller & Shifflet, 2016;Mitchell & Weber, 1998, 1999;Mitchell et al., 2011).As teachers stretch into their identities, traces of the past become "ghosts" that haunt conceptualizations about the work, intentions, and practices of teaching (Lawrence-Lightfoot, 2003, p. 3).While linked to past events, memories, like dreams, are also linked to speculative imaginations about the future (Horton & Malinowski, 2015).Both memories and dreams hover in an elusive forcefield made from material reality and imagined immateriality (Derrida & Mehlman, 1972).Remembering may well be dreamwork when it tumbles the one-remembering into the intermingled space between lived social reality and future possibilities that are not-yet.In this article, we offer dreamwork as a metaphor and method to shine light on the creative ways that prospective teachers utilize childhood memory to both affect the enduring, disquieting, and at times painful bedrock of the schooling past and imagine the pedagogical future.Our data is drawn from 116 childhood memories written by adults who were enrolled in teacher education programs and/or childhood studies courses in Canada and the United States.The memories we gathered are diverse, ranging from carefree scenes of summer picnics, first bike rides, and "innocent mischief" to frightening times when everyday mistakes, risks, and antics lead to harsh punishment and surveillance (Farley et al., 2020, p. 111).Of all the memories, we focus here on 40 memories set in the context of schools and classrooms to speculate about the lasting impact of C
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".