A Review of Housing and Food Intersections: Implications for Nurses and Nursing Research
Bibliographic record
Abstract
Study Background Quality, accessibility, and affordability of housing and food are public health and nursing concerns. Yet, intersections between housing and food security are relatively understudied. Purpose The purpose of this article is to examine the evidence describing the relationship between food security and housing interventions, and second, describing specific opportunities for targeted strategies for nursing practice and research. Methods Arksey and O’Malley’s scoping review method was followed to search housing and food security research. A database search identified 46 studies that were mapped onto a social ecological theory to understand the micro, meso, exo, and macro interventions. Results Three major recommendations were identified. Micro-system recommendations include primary care screening for low-income groups. Meso- and exo-system recommendations focus on creating partnerships in research and enhancing social housing. Lastly, macro-system recommendations focus on challenging housing affordability standards. The major gap in the literature is addressing healthy housing. Conclusion Broadening housing interventions to include comprehensive approaches to meeting individuals’ needs offers more than simply packaging two interventions together. There is a significant moment in nursing in which nurses are witness to a paradigmatic shift in the ways to approach housing and food security.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".