From Housing Stratification to Class Exploitation: Ricardo Tranjan’s “The Tenant Class” in Light of the Housing Class Theory of J. Rex and R. Moore
Bibliographic record
Abstract
The article reviews Ricardo Tranjan’s book The Tenant Class (2023), which examines housing inequality and class relations within the rental housing market. The study aligns with current developments in Canadian housing sociology, a field that is undergoing a period of active institutionalization and theoretical renewal. Tranjan advances the Marxist political economy tradition, conceptualizing tenants as a social class subjected to economic exploitation by landlords, and argues that Canada’s so-called housing crisis is not an accidental phenomenon but a stable system of power and income redistribution. The review notes that, despite the book’s conceptual proximity to the housing class theory of J.Rex and R.Moore, Tranjan does not explicitly engage with their framework, limiting his analysis to the categories of class struggle and exploitation. This narrows the book’s theoretical depth but enhances its political relevance and public resonance. The work is regarded as an important contribution to housing sociology, reintroducing the notion of “class” into both academic and public discourse and uncovering the political foundations of housing inequality. The book may be of interest to sociologists, scholars of social policy and urban studies, as well as educators and housing activists concerned with issues of affordability and tenant organizing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".