Bibliographic record
Abstract
Once again, in this its second issue, the SFU Educational Review offers a further forum for the various ideas generated at the annual Education With/Out Borders (EWOB) conference.Fiona McKeller's somewhat iconic image on the cover illustrates the dual nature of borders in both providing reasonable and directive boundaries and, by their very nature, the possibilities of breaching or bending those boundaries.Relatedly, her fascinating video of Education With/Out Borders and its genesis provides a fascinating retrospective on the evolution of EWOB, and it is interesting to see the various perspectives taken on the concept of borders, on the conference itself, and, in a larger sense, how these might define or at least question notions of scholarship and scholarly activity: a necessarily perennial and evolving consideration.This issue of the journal sees six worthy contributions whose themes overlap, covering narrative, complexity, sites of learning, and, yes, borders.Susan Barber explores the ways in which teachers' own stories can help them develop their senses of themselves as teachers; she proposes a new genre: pedagogical literature.She goes on to write: "If students who are becoming teachers can access a variety of stories about how identity is changing as they are in the process of becoming teachers, as well as learning about how they might handle situations they have not yet come across, they might be able to translate some of this knowledge into real life."Further, Barber takes a holistic approach to the roles and identities of teachers, seeing them develop in and through the relationships in the classroom and surrounding social spheres.She offers a practical end: "If students who are becoming teachers can access a variety of stories about how identity is changing as they are in the process of becoming teachers, as well as learning about how they might handle situations they have not yet come across, they might be able to translate some of this knowledge into real life."The intersections of literature, identity, and pedagogy which, interacting together, shift the borders of each.This is exactly the theme that Craig Newell works with in his paper on the applications of complexity theory to education.He asks us to consider a synergistic shift from the student to the collective class and its interactions as the systemic locus of learning.Further, in exploring the work of Brent Davies, Dennis Sumara, and Elaine Simmt, he suggests this system may be adaptive: we no longer consider individual learners but a self-organizing, collective learning system.Citing Davies and Summara, Newell notes that complexity cannot be scripted into the classroom but it can be occasioned.Just such an occasioning occurred with the publication of his paper.He had included an image of sandpipers taking off as a flock from a beach to illustrate the principle of emergence, and had found the image on the website of a Bed-and-Breakfast in New Brunswick.(One of the reviewers of Newell's paper had commented: "A beautiful and excellent choice of image to show concepts of selforganization in complex systems.")The owners of the website gave their consent to use of the image in what might represent a charming first: likely the first time the owners of a Bed-and-Breakfast have ever had their intellectual property acknowledged in an academic journal.
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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.190 | 0.127 |
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".