SMOOTH TRANSITIONS: INTEGRATING A HIGH SCHOOL AND TEACHER EDUCATION PROGRAM
Bibliographic record
Abstract
The Faculty of Education and a High School partnered for five semesters to deliver an integrated course which combines a first year teacher education course, ECS 100, with grade 12 English, Psychology and Career and Work Exploration. This project was developed to support “unlikely” students move from high school to pre-service teacher education. The purpose of the research was to develop a deeper understanding of the challenges and opportunities of this integrative approach and consider ways to support high school student’s transition into teacher education programs . T ransformational grounded theory guided data collection and analysis. Data was collected through two individual interview cycles with 23 students and one cycle of group interviews, for a total of 49 interviews. An Indigenous scholar was the critical friend throughout the study and supported the decolonizing component of the research. The findings are discussed in the context of the ways the teachers and the professor negotiated five contradictions. As the students readied themselves for teacher education, the researchers turned their gaze to wonder if teacher education structures had readied itself for diversity. The contradictions between calling for diversity and addressing structural inequities became more evident as we understood the needs of our students.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Study of a high school to teacher education transition program; professional education, not research training.
The study examines transitions between high school and teacher education programs.
Integrated high-school/teacher-education pathway study is education research, not study of scientific research systems.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".