Tenoch's Gender Journey: Case Study of a 13-year-old Mexican Refugee with Aboriginal Ancestry - Naming the Gaps Between Theory and Practice
Bibliographic record
Abstract
This paper explores the issues and technique that were used with a group of non-conforming youth to prepare them for successful entrance into university. It will produce and affirmation of the inner wisdom of non-traditional students as a mirror of learning for traditional teachers, to provide an example of dialogic learning through a de-colonizing lens. Then it will present the results of six years of group support and counselling to prove that denouncing the gaps in institutionalized systemic barriers to sexual minorities, coupled with persistent clincal, advocacy, and community activism, is effective in breaking the cycles of magrinalization of fervent, creative, and resilient youth once termed "at risk". Immigrant latino youth in general and the case study of Tenoch in particular shows that a direct application of present clinical practices are not enough to provide long-term healing and decolonizing attitudes to survive the academic needs of a border-gender communities. Regularm on-going therapy focused on anti-oppressive pracitces coupled with Aboriginal healing techniques has proved to be a valid, reliable, and consistent method to increase this vulnerable population's well-being without further marginalization. A practitioner might conclude that mixed model is more affirmative of individual process of personhood while still connected to one's roots and communities of origin. The implication of practice is that a clinical needs to also engage in advocacy, support, and profound transformations in order to unmask both inner and outer colonized mind traps.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".