What to do About (Housing) Injustice? Developing the Social Connection Model’s Prioritization and Action Guidance and Investigating Landlords’ Responsibility for Housing Injustice
Bibliographic record
Abstract
This thesis develops the prioritization guidance and action guidance provided by Iris Marion Young’s Social Connection Model of responsibility for injustice. Young’s parameters of reasoning are limited in their ability to assist responsible agents in determining what they ought to do to fulfill their responsibilities, as they are severed from the structural analysis characteristic of the rest of the SCM. This thesis addresses the resulting limitations by developing categories of prioritization and an action guidance framework. I develop 6 categories of prioritization: power, benefit, interest, centrality, contribution, and control. Applied to social-group-based analysis, these categories determine the strength of the prioritization claim which a given injustice holds over a given social group. The action guidance framework takes the perspective of the political community and works its way through three questions and their corresponding considerations: “What can we do?” –structural change, altering practices, and harm alleviation; “How can we do it?” –understanding sub-issues and sub-options, determining interests, and organizing collectives; and “What can I do?” –eliminating contributory behaviours, and considering personal circumstances. Through this framework, agents can analyze the capacities of the political community and the structures of an injustice to determine which projects should be undertaken and how agents ought to contribute. Finally, the developments of this thesis are applied to the case of landlords and housing, therein establishing the necessity of landlords abandoning rental profits so as to fulfill and not contradict their responsibility to eliminate housing injustice.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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".