A Phenomenological Investigation of the Unmet Needs of Newcomers Experiencing Insecure Housing in the Waterloo Region
Bibliographic record
Abstract
Insecure housing, like other categories of homelessness, leads to a plethora of unmet needs, yet remains hidden. Newcomers arriving in Canada within the last 10 years are particularly vulnerable to experiencing homelessness but are understudied. The purpose of this study was to investigate the unmet needs of newcomers experiencing insecure housing in the Waterloo Region, Canada. Using interpretive phenomenology, semi-structured interviews were conducted with 10 participants. Interviews revealed unmet health needs related to food insecurity and lack of health insurance coverage, including meal avoidance, compromised food quality, medical noncompliance, and costly health service avoidance. Unmet employment needs emerged due to frequent unemployment and underemployment despite high levels of education. The settlement process directly contributed to unmet employment needs for newcomers that were not international students by restricting employment with long wait time for work permits. Without work permits, newcomers were forced to accept inadequate funds from Ontario Works. While well-intentioned, community and government supports could not adequately support newcomers in insecure housing situations due to limited knowledge of newcomers, lack of guidance during the settlement process, and broken connections between community service agencies. Recommendations include improving the timeliness of work permits, increasing the funding from Ontario Works, amending Ontario Health Insurance Plan to cover health costs for newcomers waiting for work permits, wrap-around services for newcomers in the Waterloo Region, and interventions in post-secondary institutions to address food insecurity and inadequate health insurance coverage for international students.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".