Policy responses to youth homelessness: Ireland and Flanders compared
Bibliographic record
Abstract
Background: Youth homelessness is a global problem and the situations and needs of young people who experience homelessness are increasingly recognized as distinct from those of their adult counterparts. Correspondingly, responses to youth homelessness have shifted in many countries, with policy and interventions increasingly directing the weight of attention toward prevention, alongside initiatives designed to move young people out of homelessness services and into housing as soon as possible. Within the literature, however, relative to analyses of policies targeting adult homeless populations, comparative research on youth homelessness policy is very under-developed. Aim: This paper examines youth homelessness in Ireland and Flanders, Belgium, reviewing the scale and nature of the problem and examining policy responses to youth homelessness in both jurisdictions. Results: Findings reveal many parallels in the scale and drivers of youth homelessness Ireland and Flanders. Policy has evolved at a faster pace in Ireland, where there has been far more substantial investment in the development of strategic approaches to tackling the problem of youth homelessness. In both Ireland and Flanders, there is evidence that policy has not adequately addressed the structural causes of youth homelessness, including the lack of affordable housing and migration, as an emerging structural driver of homelessness among young people. Gendered homelessness is not explicitly addressed within youth homelessness policy in either Ireland or Flanders despite the strong presence of young women in their respective homeless populations. Conclusion: The paper concludes by discussing the key issues and lessons arising from the paper’s analysis, particularly in terms of realizing the goal of providing sustainable housing solutions for young people who experience homelessness. Youth homelessness is a global social problem that has grown in scale in many European countries over the past decade ( FEANTSA, 2017a , FEANTSA, 2018 ). Rising numbers of youth have also been recorded as homeless in the US, Canada and Australia (Australian Housing and Urban Research Institute, 2020; Gaetz et al., 2016 , The U.S. Department of Housing and Urban Development, 2021 ). As a population, young people who become homeless are known to have experienced pre-homelessness adversities, often spanning from childhood, with large numbers reporting family conflict and breakdown, experiences of abuse and/or violence, disrupted schooling, and histories of state care ( Davies and Allen, 2017 , Embleton et al., 2016 , Grattan et al., 2022 , Morton et al., 2018 ). In several countries, LGBTQI+, Indigenous and migrant youth have been identified as at higher risk of homelessness ( Ecker et al., 2019 , FEANTSA, 2017b , Kidd et al., 2019 , Shelton et al., 2020 , Baptista et al., 2016 ). Irrespective of their family and personal characteristics, poverty is a factor that unites youth who experience homelessness ( Embleton et al., 2016 , Mayock and Parker, 2023 ), with structural and economic disadvantage creating the conditions that work, alongside other factors, to push young people out of home.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".