‘Don’t wake papa bear!’ Understanding media representations of landlord-tenant relations
Bibliographic record
Abstract
Landlord–tenant relations are one of the core social relations of daily life yet are surprisingly under-theorized by housing scholars and geographers. This article begins to address this gap by applying for feminist scholarship on hegemonic masculinity and emphasized femininity to the case of the expansion and subsequent retrenchment of rent-control policy in Ontario, Canada in 2017–2018. Through a discourse analysis of government policy documents and news media coverage, I demonstrate that portrayals of landlords and tenants broadly conformed to characteristics of hegemonic masculinity and emphasized femininity, respectively, with landlords most commonly portrayed as ‘rational’ and tenants most commonly portrayed as ‘vulnerable’. Landlords benefit from traits associated with hegemonic masculinity even if they themselves do not embody them. Similarly, landlords benefit from the portrayal of tenants as passive victims, in need of paternalistic government protection, as opposed to potentially powerful collective actors.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".