What I Want My Teachers to Know: The Lived Experiences of Adolescents with Fetal Alcohol Spectrum Disorder
Bibliographic record
Abstract
Fetal Alcohol Spectrum Disorder (FASD) is a diagnostic term used to describe impacts resulting from alcohol exposure during prenatal development. Individuals with FASD have strengths they can use in and out of the classroom, yet much of the current FASD literature has largely focused on personal deficiencies such as deficits in thinking abilities, and challenges with behavioural functioning and emotional regulation. This study employed a qualitative descriptive design. Semi-structured interviews approximately 30 minutes in length were conducted with two adolescents from Alberta, ages 13 and 15, with FASD. These adolescents voiced what they wanted teachers to know about their perceived strengths and struggles across school, home, and community settings. Interviews were audio recorded using Google Meet, transcribed, and analyzed using thematic analysis. Interview data provided insight into lived experiences including the strengths adolescents with FASD have and the struggles they experience in and out of school settings. By engaging individuals with lived experiences, more can be learned about the unique perspectives of adolescents with FASD. Results revealed adolescents with FASD want teachers to know (1) they are aware of some ways to manage their emotions and some of what adds to their struggles, (2) they have preferences for the ways they learn, and (3) they value and desire meaningful relationships. These findings provide insight into how teachers can position themselves to provide high-quality instruction and specialized support for adolescents with FASD and appreciate the unique strengths and interests adolescents with FASD have to offer.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".