Affirmation and Safety: An Intersectional Analysis of Trans and Nonbinary Youths in Quebec
Bibliographic record
Abstract
Abstract This article presents the results of a combined grounded theory and community-based participatory action research project with 54 trans and nonbinary youths (TNBY) residing in the province of Quebec, Canada. The project includes two important sensitizing concepts: intersectionality and recognition. In the research, intersectionality was defined as an approach that explores how people navigate manifold identities (class, race, disability, and so on) in the context of structural oppression. Authors applied an intersectional lens to the recruitment of research participants through an iterative, community-based process, and to the analysis of the oppressive structures that negatively influence the well-being of TNBY and the specific factors that enable TNBY to thrive. Drawing on Honneth’s concept of recognition, authors argue for a contextualized, dynamic, and relational understanding of how well-being is produced. Specifically, they show two presenting needs: one for affirmation and one for safety, access to which springs from resources of privilege that emerge in the environment in which young people are embedded and from which they self-advocate. Understanding the dynamic relationship between these two needs and how they shift according to context is an important component of applying an intersectional approach to supporting TNBY in social work settings.
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 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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.024 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".