Stories from the First Cohort in Doctor of Education in Distance Education
Bibliographic record
Abstract
The first cohort in the Doctor of Education in Distance Education at Athabasca University began in August 2008. From the first two years of this program, there are experiences for reflection and stories to be told from this community of online learners. Storytelling offers a reflective tool for constructing meaning to inform practice and pedagogy and provides a legacy for future online doctoral students in distance education. La premiere cohorte au programme de doctorat en Education a distance a l’Universite d’Athabasca a debutee en aout 2008. Sont issues des deux premieres annees de ce programme, des experiences qui portent a reflechir et des histoires a raconter au sujet de cette communaute d’eleves en ligne. La narration d’histoires peut ainsi etre un outil de reflexion permettant l’elaboration de connaissances qui contribuent a la pratique et a la pedagogie et elle permet de laisser en heritage aux futurs etudiants au doctorat en ligne, des lecons a tirer sur l’education a distance.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".