Politics of the Past: Understanding the Role of Memory, Postmemory, and Remembrance in Navigating the History of Migrant Families
Bibliographic record
Abstract
The importance of history as an HCI method has been gaining increasing attention in HCI literature. However, the mainstream historical sources (books, documentaries, etc.) and methods often risk (re)producing western colonial biases potentially providing a narrow one-sided perspective on history and detaching “sanitized facts” from people’s emotional accounts. While oral history and similar alternative methods are often used as a countermeasure, their applicability has remained underexplored in HCI, especially in a sensitive context, such as migration. We build on the rich body of social science work on collective memory to introduce a complementary way of navigating the past of the migrant families, and also reveal the corresponding challenges to advance this literature. Our interview study with 17 migrant families highlights how the politics of remembrance, family dynamics, and postmemory shape the past stories of migrant families. We discuss how these findings inform the HCI literature on migration, design, and postcolonial computing.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.024 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".