Bibliographic record
Abstract
An image of a snowflake adorns the cover of this issue. It also serves as a guiding metaphor for our editorial discussion. The twelve articles in this issue have been gathered over two years and come from varying perspectives on a variety of topics pertinent to the study of curriculum. Each article was developed using a distinct research practice. Like snowflakes, each article is unique, nuanced with individuality. And yet, like snowflakes, there are recognizable patterns that repeat across the articles of this issue. As we read about issues of colonial alienation of First Nation communities, COVID restrictions, financial literacy gaps and student distress, we observe recurring psychological and social processes. And these processes show fascinating parallels to the molecular dynamics of snow crystal formation! For example, we see the impact of the environment on the process of learning. We see the benefit of an interactive, adaptive, relational pedagogy centred on care. And we see the value of viewing things from a different perspective, through a different taxonomy. The metaphor of the snowflake shows us richness in diversity, and it also reminds us that a genuine conversation will reveal unity across difference.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".