From Shinjuku to River John: The neoliberal juggernaut, efficiency, and small rural schools
Bibliographic record
Abstract
It may seem a bit odd to begin an article that introduces a series of pieces about small ruralschools in Canada, Norway and in Australia by referring to Tokyos Shinjuku Station; but that ishow I want to begin. Shinjuku is the worlds busiest railway station, moving approximately 3.4million people each day through its turnstiles. I was there last summer. One of the great ironiesof being a scholar of rural education is that I am able to go to major urban centres to speakabout my research in small rural places. Shinjuku is a fascinating place, remarkably efficient anda feat of modern engineering. I lived for a time in a small town, rural railway station with myfamily in southwestern Nova Scotia. My father was a railway stationmaster, and I worked myway through university laboring on track gangs in the summers. I love trains. Im a bit of anefficiency expert because my experience working for the Canadian National Railway trained meto think in terms of safety and efficiency.
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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) | 0.000 | 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".