Nomads in a petro-empire: Nenets reindeer herders and Russian oil workers in an era of flexible capitalism
Bibliographic record
Abstract
Although the process of writing a dissertation often feels like an incredibly lonely one, the completion of doctoral studies in anthropology involves many more people than the student himself.Over the years of my doctoral studies, I received the help and support of a great number of people.I first wish to express my deepest gratitude to the people in the Nenets Autonomous Okrug (NAO) who welcomed me into their lives and/or took part in my research, be it in the capital, Naryan-Mar, on the island of Kolguev or in the Bolshezemelskaya tundra.I am especially thankful to the reindeer herders and the administrators of the Kharp and Kolguev agricultural cooperatives.I am also extremely grateful to my friends in Moscow, who were always available to host me whenever I was on my way to or from the NAO.For reasons discussed in the introduction, I prefer not to name those in Russia who should be thanked the most.I did thank you in person, and will remain ever grateful for having been so hospitable and generous to me.This research would also not have been possible without the support of the administration of the Nenets Autonomous Okrug.I wish to thank more particularly the Department of Foreign Relations.It has always been such a pleasure to arrive in Naryan-Mar and feel the encouragement and support of the people in that office.I am most especially thankful to Dmitrii E. Medvedev.At my university, I owe much to my supervisor, Ronald Niezen, who immediately became interested in my research project when I initially approached him.Over the years and the different phases of what doctoral studies in anthropology entail, he has provided me with constant support.Of particular importance to me was that he found the right balance between a very helpful guidance, and trusting that my intuition and reflections were going somewhere.I must also thank Juliet Johnson from McGill's Department of Political Science.She was always available to discuss various aspects of my work, while also being very encouraging and motivated by the anthropological nature of this project.John Galaty at my
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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 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".