Wonderland for Wolves: A Sociography of Chornobyl
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
I was writing about the Chernobyl Exclusion Zone when the global pandemic of Covid-19 hit. Everywhere I looked news articles crowded with infographics of the infected made me suspicious of spheres: curves needed flattening. No matter where I turned for information there were human shapes in rings marking distance. I was disturbed by how often the phrase ‘what goes around comes around’ popped into my head, like some kind of self-hazing ritual initiating me into a new normal. As I send this sociography to publication, Russia has invaded Ukraine. The Chernobyl Zone, along with the rest of the country, has become a battlefield. There is no other way for me to write this, from a distance, other than to do so through a looping disorientation. And so I write by turning paragraphs into zones that surround ideas, memories, facts, and feelings of place that are never stable, but always on the move.
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.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it