‘Models of possible selves: teachers’ reflections on childhood memories of parents’
Bibliographic record
Abstract
This study draws from theories of attachment to examine prospective teachers’ reflections on the role of the parent in their childhood memories in shaping the imagination of their future selves. As part of a larger qualitative study, we collected and analyzed the memory narratives of teacher candidates and undergraduate students preparing to work with children, and selected 53 of the 116 narratives that featured parents. These memories demonstrate three ways in which parents figured into the participants’memories and reflections on their motivations to work with children: 1) as supportive role models, 2) as catalysts of sympathy for children whom teachers imagine as lacking the privileges their own parents provided, and 3) as spurs for empathy towards children whom they identify with as experiencing challenging situations. In each case, the participant created an internal working model of the child-adult relationship in their memory and imagined themselves taking up a parallel role as the adult in a future child-adult relationship. As teacher educators concerned with the identity work of preservice teachers, our findings highlight the importance of critically exploring childhood memories of parents as models for the teacher-child relationship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".