Cariño in the Borderlands: Pedagogical Relationships in a Community-Based Education Support Program
Bibliographic record
Abstract
This dissertation examines the development of pedagogical relationships between tutor mentors and students, parents, and staff in a tutoring and mentoring program dedicated to decreasing the push-out rates among students of Spanish- and/or Portuguese-speaking descent in the Toronto public school system. Using a Transnational Latina Feminist framework, I examine program documents, observation and interview data to understand how these relationships develop, and how tutor mentors navigate issues of cultural and linguistic identity in these relationships. Furthermore, I examine how discourses of identity and community are articulated by the tutor mentors in the development of these relationships. Identity featured prominently in participant narratives, and participation in the program was often positioned as an enactment of cultural identification. I found that discourses of linguistic and ethnic identity were often conflated in participant narratives, constructing a homogenous community of Portuguese-speakers at the exclusion of other lusophones in the city. Latinx tutor mentors identifications as Latinxs featured prominently as motivators to enter the program and engage in these mentoring relationships with their students. Discourses of community critically shaped the program, which utilized its relationships with the Lusophone and Latinx communities to function as a bridge between the communities and an alienating school system. Thereby providing important spaces for the creation of counter-narrative for the parents in the community, building the social capital necessary for Lusophone and Latinx families to effectively engage with the education system. Authentic caring relationships, characterized by cariño and the consejos were a critical part of the program experience. These relationships provided a positive learning environment for students, as well as a place for tutor mentors to heal from their own negative schooling pasts. This dissertation contributes to our understandings of the importance of relationships in pedagogy, and how these relationships can help educators to heal from past experiences. I highlight the benefits of community-based education. My dissertation contributes to the growing fields of Latinx-Canadian and Luso-Canadian studies. I also offer a different reading on Latinidad as it is lived in Canada and how the different reading of the Canadian context can enrich our understandings of mestizxs.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 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".