Debating and managing homelessness through discourse: News media representations in Montreal (1991-2019)
Bibliographic record
Abstract
This study examines representations of homelessness in two Montreal newspapers, The Gazette and La Presse, across three decades (1991-2019). Grounded in social constructionism, it employs a critical discourse analysis to identify recurring and emerging discursive themes related to problematizations, responses and proposed solutions, portrayals of people experiencing homelessness, causal attributions, and voices included as claims-makers. This research contributes new insights to the study of media discourses of homelessness by extending longitudinal analysis into the 2010s and focusing on Montreal, an under examined context in English scholarship. Despite the adoption of supportive policy response in recent years – and despite variations across decades and newspapers – the findings reveal a persistent tendency to portray homelessness through individualizing and moralizing narratives with emphases on management and control. The study examines the limitations of discursive shifts when they occur within and alongside these enduring dominant representations, highlighting how even seemingly progressive narratives can reinforce logics of poverty management. It concludes by considering possible implications of these persistent discursive patterns
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 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".