Digital Storytelling with First Nations Emerging Adults in Extensions of Care and Transitioning from Care in Manitoba
Bibliographic record
Abstract
This study investigated the experiences of emerging First Nations adults in extensions of care and transitioning out of care in Manitoba. Four research questions were explored in this study: 1) What do you remember about your time in care and what was your transitioning experience out of care or upon reaching 18 years of age? 2) What challenges, barriers or opportunities have you experienced since leaving care or turning 18? 3) How have you maintained the connection to family, community and culture since transitioning out of care? 4) Do you think you have reached adulthood? These questions were discussed through two digital storytelling workshops where over the course of five days participants developed and embedded individual responses to these questions into their own digital video. Follow up interviews were conducted with the participants to get feedback on their perspectives and evaluation about the digital storytelling workshops. Digital storytelling, through the art of combining oral tradition with digital technology, is a participatory, arts-based, learner-centered approach to generating knowledge. It involves using computer software to create a three to five minute video to illustrate a personal history. The findings suggest that Indigenous emerging adults in extensions of care and transitioning from care in Manitoba continue to experience difficulties on their journeys toward adulthood. However, the findings also suggest that the participants in this study are resilient despite the fact that they are dealing simultaneously with memories of being in care, negative peer pressures and problems in getting their basic needs met as they navigate life beyond their child welfare experiences. This study enhances the understanding of First Nations young peoples’ experiences in extensions of care and as they transition out of foster care, and contributes to the growing body of knowledge that utilizes digital storytelling as a contemporary method conducive to working with Indigenous emerging adult populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".