The Invisibilised Labour of Diasporas as Co-sponsors in Refugee Sponsorship: Lessons <i>From</i> Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract For almost 45 years, civil society groups have volunteered their time, energy, and finances to resettle more than 327,000 refugees through Canada’s Private Sponsorship of Refugees programme. Sponsorships are commonly arranged by local communities, faith-based organisations, or private citizens who have entered into agreements with the federal government. Much of this effort is supported by former refugees who were themselves resettled to Canada. Yet, the existing literature underrepresents the crucial role of sponsors with refugee histories. This research examines the previously invisibilised labour of diasporic sponsors, highlighting the unique and vital role stemming from their dual social locations as former refugees and private sponsors. Through participant testimony from in-depth, semi-structured interviews and triangulated document analysis of policy and programmatic data, this research finds that invisibilisation lies at the administrative level of sponsorship processes. This includes the interactions between Sponsorship Agreement Holders and co-sponsor mechanisms, and how formalised and less formalised processes play out. The co-sponsorship model illuminates the nuances and possibilities for sponsorship sustainability beyond the courte durée, emphasising the vital labour of diasporic sponsors in this dynamic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it