Bibliographic record
Abstract
Summary “The election” tells the story of the 2000 regional election in Chukotka, Russia's northeasternmost part. That year, Lyosha, a Chukchi activist, invited me to assist Indigenous movements with grant writing for Western‐based civil society organizations. When I arrived in Chukotka, the election was in full swing and turned out to be more bizarre as—as Lyosha put it—could be believed. The gifting of the oligarch, the lies told by the governor, the dreaming of Lyosha, and the interrogation of the anthropologist are all things that happened, and I wanted to tell their story. But I also wanted to describe what did not happen: the democracy that was not desired or embraced. The result, I hope, is a story that shows not only what it felt like to be part of this election but also what Russia was at that time, why it has possibly become what it has become, and how and why elections leave ghosts. The narrative form has been inspired by the Russian literary tradition of the skaz , an absurdist form of narrative where things rarely are what they pretend to be.
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 | 0.001 | 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 | 0.027 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.009 |
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".