Reflective Practice in Homelessness Research and Practice: Implications for Researchers and Practitioners in the Covid-19 Pandemic Era
Bibliographic record
Abstract
This discussion paper focuses on “reflective practice” as conceptualized by Donald Schön with its particular application in homelessness research and practice. Reflective practices are slowly gaining ground among scholars and practitioners engaged in the homelessness sector since the onset of the pandemic where increasing reliance on tele-mediated communication has transformed the ways in which research and practice take place. This paper starts by revisiting the concept of reflection as propounded by John Dewey and later recalibrated by Donald Schön, followed by a discussion of how two specific reflective practices, namely reflection-in-action and reflection-on-action, can be leveraged in homelessness research and practice. The paper concludes by discussing some implications of such practices for researchers and practitioners involved in the homelessness sector in the pandemic era. These implications focus on issues such as housing affordability and affordable housing, case management and support services, and barriers caused by the pandemic to homelessness research.
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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 | 0.289 | 0.221 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.022 | 0.123 |
| Scholarly communication | 0.040 | 0.041 |
| Open science | 0.007 | 0.034 |
| Research integrity | 0.017 | 0.021 |
| 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".