From strict socialism to social evils: Changing childhoods over three generations in urban Vietnam
Bibliographic record
Abstract
Abstract Over the span of three generations, Vietnam's capital Hanoi, has transformed from a modest city grappling with food scarcity during the socialist subsidy era to a sprawling metropolis marked by gated communities and a widening wealth divide. Employing a child‐centric, multi‐generational family methodology, with members of 13 families across three generations, we explore the diverse childhood experiences shaped by these rapid urban transformations. Grandparents shared stories of unrestricted outdoor play despite challenging conditions, while parents noted a lack of academic pressures in their youth. Contemporary children enjoy access to new technology and consumer goods, but face important mobility restrictions due to parental and societal concerns. Our findings reveal that the Vietnamese context engendered distinctive childhood reflections for the two older generations, contrasting with childhoods in non‐socialist contexts during the same periods. Meanwhile, the contemporary Vietnamese state has crafted a ‘social evils’ discourse that shapes current childhood opportunities in specific ways. By being centered on urban Vietnam—a context vastly different from Global North‐dominated narratives in childhood studies—our study acts as a counterpoint that enriches the field with perspectives from a politically‐socialist state. Focusing on the unique childhood experiences within Hanoi's evolving socio‐spatial landscape, we advocate for more diverse understandings of childhood that respect varied realities across contexts.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".