STEPPING OUT OF THE DIRT: A CASE STUDY OF THE IMPACT OF REFLECTIVE EXPRESSIVE WRITING ON MALE TEENS RECENTLY RELEASED FROM A CLOSED CUSTODY FACILITY
Bibliographic record
Abstract
When researching the topic of at-risk youth and reflective expressive writing there is little literature to be found. The limited literature that exists with regards to reflective expressive writing is not geared toward a population of at-risk teens (Burton & King, 2004). Although there is literature on alternative programming for at-risk youth (McKee & MacDonald, 2006), very little discusses reflective writing. The research question being addressed is: What is the impact of reflective expressive writing on male teens that have recently been released from a closed custody facility? The aim of this study is to present rich descriptive narratives that allow for future researchers, community members and educators to come to an understanding of the resources that youth may benefit from in both traditional and alternative learning environments. The following case studies examine the stories and experiences of two young men, ages 19 and 16, who took part in a reflective expressive writing initiative. Both young men who participated in the study are from Southern Ontario and were released from the same closed custody facility. A description of their experiences is provided and key themes that emerged from the analysis of journals, interviews, conversations, and field notes are also examined. The provided themes are areas of focus that proved meaningful when discussing the writing and reflecting that occurred. Four primary themes are discussed: relationships, depth of reflection, sense of belonging to a community, and self-esteem. Specific to the youths’ relationships there are five sub-themes that are presented: determining characteristics, family, friendship, mentorship, and the researcher. Therefore this study responds to Long and King’s (2011) call for greater attention to alternative learning programs to support at risk youth. Concluding remarks present the ways in which educators and community programs can engage at-risk male youth in respectful and trusting relationships.
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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".