Immigrant Children's Bodily Engagement in Accessing Their Lived Experiences of Immigration: Creating Poly-Media Descriptive Texts
Bibliographic record
Abstract
In this paper, we explore the role of the lived body in meaningful understanding beyond linguistic conceptualization in phenomenologically oriented inquiries. In this exploration we consider the role of visuality (i.e., still photography) and enactment (i.e., tableau) as possibilities for accessing meaning beyond language-bound descriptions of the phenomenon of moving childhoods--that is, children's lived experiences of immigration. We suggest that immigration is an experience that interrupts the familiarity of the lifeworld, and thus brings immigrant children's awareness of their bodies to a conscious level. We ask: What methods of inquiry can be used to access more directly the "embodied understanding" and, in particular, the lifeworlds of immigrant children as they leave the familiar "home world" and enter the "alien world" of a new school? In addressing this question, we focus on one aspect of phenomenological inquiry--gathering experiential accounts, or lived experience descriptions, in investigating childhood phenomena--which presents a particular challenge to researchers working with young children. We present an example of a method that bridges hermeneutic phenomenology and arts-based research methodology (i.e., fotonovela) developed specifically to engage immigrant children bodily in accessing their lived experiences of their first day of school in the host country, and in the development of a polymedia text showing these experiences. We believe that the example demonstrates how fotonovela facilitates immigrant children’s recollection of and reflection on their experience of being at the door of a new classroom. Moreover, the production of visual texts, when shared with or read by others, has an evocative power similar to that of a phenomenological text. Thus, we argue, fotonovela is a particularly suitable method for engaging children in developing polymedia descriptive texts about their lived experiences.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".