Neither Here Nor There? Place and Placemaking in the Lives of Separated Children
Bibliographic record
Abstract
Of the approximate 18 million refugees worldwide, between 2 and 5% are estimated to be separated children, a figure which represents between 360,000 and 900,000 children. Place and placemaking represent vital components and realities during flight. The concept of place addresses the physical and social environments within which separated children move through and live in. Place and placemaking both include elements of physical setting, activity, and meaning, with placemaking specifically constituting the act of transforming the places one finds oneself into the places in which one lives. Drawing upon in-depth interviews and a focus group with 17 youth respondents living in Canada, this paper explores the realities of place and placemaking in the lives of separated children. In particular, the paper highlights the meaning and significance of place during flight. It examines the ways in which respondents 'made place' in contexts of violence and insecurity through social networks, through reliance on language and cultural traditions, and through place attachment and identity. Uncertainty continues to surround the concept and meaning of place and placemaking in large part due to their contextual and subjective nature. Furthermore, the notion of place is often under-explored and under-theorized when considering separated children’s experiences and realities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.036 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".