Equality of Condition? Exploring Minority Ethnic Group Experiences of Education in Northern Ireland
Bibliographic record
Abstract
The period since the signing of the Belfast/Good Friday Agreement in 1998 has seen an exponential rise in inward migration to Northern Ireland, with around 8% of the school-age population now comprising children and young people from minority ethnic groups. In this paper, we examine the experiences of families from minority backgrounds, including recent migrants and those from generations previously settled in Northern Ireland, as they navigate school choice and the transition from primary to post-primary education in a system characterised by academic selection and denominational segregation. Drawing on an ‘equality of condition’ framework, relating to the purposes and processes of education (Lynch and Baker, 2005), and adopting a qualitative approach, our findings highlight the interplay between identity categories, accrued or accessed social, educational, economic capital, and formal and informal power structures in mediating school experience. We propose that dimensions and intersections within this dynamic may contribute to equality of condition deficit for some minority families as they seek to secure primary and post-primary school placement for their children.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.010 |
| 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".