Bibliographic record
Abstract
Includes a prize-winning chapter by the winner of the 2021 Early Career Award of the International Narrative Research Special Interest Group of the American Education Research Association. Trudy Cardinal was awarded this prize, among other publications, for chapter 11 in The Doctoral Journey: International Educationalist Perspectives: An Autobiographical Narrative Inquiry into the Experiences of One Cree/Métis Doctoral Student. This book has prompted an expanded book series: The Doctoral Journey in Education. Please click here to find out more! The Doctoral Journey: International Educationalist Perspectives assembles a collective narrative related to the doctoral journey of recent graduates in the field of education. Clearly, the doctoral journey is not a linear process but rather a lattice of ever-evolving professional and personal relationships, experiences, perspectives, and insights. From early on when considering whether or not to apply to a programme, to deciding on an institution and supervisor, to delving into the related literature, to data collection and analyses, to closing in on the defence, to results dissemination, and everything in between and beyond, the doctoral journey presents incalculable obstacles that can be, and have been, overcome by doctoral graduates—including the contributors in this inspirationally-sparked collective narrative. Contributors are: Trudy Cardinal, Philip Wing Keung Chan, José da Costa, Alison Egan, Janet McConaghy, June McConaghy, Kelsey McEntyre, Sammy M. Mutisya, Christina A. Parker, Carla L. Peck, Colin G. Pennington, Kathleen Pithouse-Morgan, Edgar Schmidt, and Pearl Subban.
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 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 | 0.001 | 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) | 0.006 | 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; both teacher heads agree on what is shown here.
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".