The Transformative Potential of Walls to Bridges: My Journey into Becoming a Whole Self
Bibliographic record
Abstract
Our modern disjointed society facilitates the creation of fragmented identities among its citizens.Throughout our daily lives we traverse multiple and diverse settings, meeting diff erent people with diff erent expectations, values, and perspectives.For many years, I had a fragmented personality, only showing people certain aspects of who I am depending on the context I was in.Rather than expressing my identity as a unifi ed whole, I shared the mental, physical, emotional, and spiritual aspects of myself in specifi c times and settings with select people depending on presumed social norms and expectations.This fragmented self-expression disrupted my identity development, leading to mental and emotional distress, as well as unhealthy relationships.My experiences of trauma, addiction, violence, and incarceration are examples of what Paulo Freire refers to as "limit situations", which contributed to inhibiting the development of a cohesive identity.Themes of identity politics and limit situations are explored here through an evocative approach to autoethnography, which is a particularly valuable methodology for research and writing conducted by scholars with a lived experience of incarceration.While imprisoned in a Canadian federal prison, it was through my involvement with the Walls to Bridges (W2B) program that I learned how to become my whole self, merging my mental, physical, emotional, and spiritual identities into a single entity via W2B pedagogy and praxis.Becoming my whole self was an act of liberationfreedom from hiding parts of who I am and the freedom to be who I am meant to be.In this autoethnographic essay chronicling my journey with W2B from prison to the community, I integrate literature with my experiences to highlight some positive impacts and the transformative potential of Walls to Bridges.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.050 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".