Emerging Horizons, Part Four. Derek’s Story: More Than Words
Bibliographic record
Abstract
This fourth installment of the Emerging Horizons series explores Derek’s digital storytelling (DST) experience (please see the introductory editorial, Crafting Meaning, Cultivating Understanding, to access the documentary film on which the series is based). In contrast to other workshop participants, Derek’s primary goal for his digital story was to convey a specific, pre-determined meaningful moment from his cancer experience in a more compelling manner. Building from the image system Derek utilized in his digital story, and further contextualizing the events he describes, this interpretive article depicts the unique cancer survivorship experiences of Adolescent and Young Adult (AYA) cancer survivors and demonstrates the possibilities of DST to help AYAs release “bottled up” emotions before they become rancid (i.e., release suppressed or repressed emotions before they transform into diagnosed psychosocial co-morbidity). Finally, Derek’s experience demonstrates how the multi-modal nature of DST can enable AYAs to incite an emotional response from their audience that can in turn confirm and affirm the life lessons embedded in their cancer experience.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".