Social Housing Competencies: Expertise for a New Era
Bibliographic record
Abstract
This article outlines organizational-level competencies within the changing social housing context in Ontario. The changing context is occurring at the same time as key board members and staff are retiring. This prompts the question of how the sector can ensure excellent housing for low- and middle-income tenants into the future, while keeping in mind its social justice origins. Social constructionist, adult education, and critical theoretical traditions guided the research questions and methodology of this study, resulting in a working definition of organizational competencies. Organizational competencies have been identified through a sequential mixed methods approach. Four key competency clusters have been identified: capital asset, sectoral operational, people-oriented, and strategic. These clusters and the competencies they contain provide a model to assist organizations in meeting their social justice and business goals into the future.RÉSUMÉCet article décrit les compétences organisationnelles requises dans le domaine du logement social en Ontario dans un contexte changeant. Ce contexte change en même temps que des membres clés de conseils d’administration et des employés clés sont en train de prendre leur retraite. Ces circonstances font réfléchir sur comment le secteur pourra continuer à fournir des logements désirables aux locataires à faible ou moyen revenu tout en respectant les principes de justice sociale. Pour cette étude, les traditions de construction sociale, d’éducation pour adultes et de théorie critique ont guidé la formulation de questions de recherche et la méthodologie, avec comme résultat une définition pratique de ce que sont les compétences organisationnelles. Ces dernières ont été identifiées au moyen d’une recherche par méthodes mixtes séquentielles. Quatre regroupements de compétences clés ont été cernés : actif immobilisé, opération par secteurs, service au public, et stratégie. Ces regroupements et les compétences qu’ils privilégient peuvent servir de modèles pour aider les organisations à rencontrer leurs futurs objectifs en justice sociale et en affaires.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".