Refugee community organisations: capabilities, interactions and limitations
Bibliographic record
Abstract
This article focuses on ways in which refugee-led community organisations (RCOs) carve out a space of influence through civic activism in the migration architectures of receiving countries. Building on scholarship addressing migration governance and grassroots refugee organisations, it argues that RCOs have become vital in the refugees’ search for means to alleviate the sufferings of their fellows, to empower their community and claim rights for an improvement of their conditions. The notions of invented and invited spaces are convenient to describe opportunities, limitations and the ways of interactions encountered by emerging formal and informal RCOs. Drawing on qualitative data obtained from Syrian RCOs and governance actors in Turkey, the article demonstrates how increasing numbers of RCOs operate in the invited spaces opened by the state agencies and international donors. Only rarely, however, are RCOs able to invent spaces to change existing power relations, as Turkey’s political context categorically opposes rights-based advocacy of any marginalised group, and the national refugee governance is based on temporary protection. The findings can serve to analyse the dynamics of new refugee groups’ collective actions as well as their interactions with governance actors at transnational, national and local levels.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".