A Social Justice Perspective on Strengths-Based Approaches: Exploring Educators' Perspectives and Practices.
Bibliographic record
Abstract
What does it mean to engage in strengths-based (SB) approaches from a social justice perspective? In this paper we explore the accounts of educators who work with youth experiencing social and educational barriers to describe what it might mean to engage in SB practices from a social justice perspective. Using data generated from interviews, we draw on educators ’ perspectives and reported practices to inform our conceptual understanding of a SB social justice approach. We propose that a social justice perspective of SB educational work involves at least four interconnecting sets of practices: recognizing students-in-context, critically engaging strengths and positivity, nurturing democratic relations, and enacting creative and flexible pedagogies. We contend that these interrelated sets of practices are necessary for youth to engage more fully in schooling. Key words: Social justice; strengths, youth, students deemed to be ‘at risk’, educator perspectives Résumé Que cela signifie-t-il de s'engager dans des approches basées sur les points forts du point de vue de la justice sociale? Dans cet article, nous étudions les récits d'éducateurs qui travaillent avec des jeunes et qui se confrontent à des barrières sociales et éducatives, pour décrire ce que pourrait signifier de s'engager dans des pratiques basées sur les point forts dans une perspective de justice sociale. En utilisant les données générées à partir d'entrevues, nous nous appuyons sur les perspectives de ces éducateurs et faisons état des pratiques pour renseigner notre compréhension conceptuelle d'une approche basée sur les points forts du point de vue de la justice sociale. Nous proposons que dans une perspective de justice sociale tout travail éducatif basé sur les points forts implique au moins quatre ensembles de pratiques interconnectés: la reconnaissance des élèves en contexte, l'engagement critique du potentiel et de la positivité, le
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".