Bibliographic record
Abstract
Part 1. MOBILITIES AND INTIMACIESWriting a book is a unique labor of love.The labor for this book project has extended well over a decade, so the list of those to whom I am indebted is quite long and diverse.The project would never have come into being without the inspiring entrepreneurial spirit of central Siberian women I met in the early 1990s, who were traveling across borders to supply their communities with clothing.Likewise, my research benefited immensely from the generosity of numerous women involved in the shuttle trade or working as labor migrants from Russia, southern Moldova, Ukraine, and Belarus.I owe a special thanks to those identified here as Kara, Bella, Zina, Maria, Eva, and Nelli for introducing me to their circles, as well as for providing me with something equally precious, their friendship.Maria's, Zina's, and Nelli's families warmly welcomed me and my family in Istanbul, Moscow, and Moldova as this project extended through the years.A number of sources of funding supported research and writing.The Humanities and Social Sciences (HSS) fund at the University of British Columbia (UBC), the Peter Wall Institute for Advanced Studies at UBC, and the International Research and Exchanges Board (IREX) provided support early on (2001)(2002)(2003).The Social Science and Humanities Research Council (SSHRC) of Canada provided generous funding between 2002 and 2006, making it possible to conduct research spanning three countries, including by covering expenses to have my infant daughter accompany me.The UBC Killam Faculty Research Fellowship supported my sabbatical leave in Turkey (2007), and the UBC Arts Undergraduate Research Award (AURA) supported several undergraduate students to do library research.Finally, in 2016 I was fortunate to receive the UBC Dean of Arts Faculty Research Award, a form of support that could not have come at a better time; the award enabled me to set aside teaching and administrative duties for one term and focus on completing the manuscript.$1,000 to purchase merchandise on each trip.In this way, the "shuttle traders" ( chelnoki ), or "suitcase" traders, most often women, literally transported goods back to community street markets in suitcases.14 By 1996, however, government restrictions on imports into post-Soviet countries made the shuttle trade unprofitable for all but those with sufficient capital to pay for the services of shipping companies able to evade the high government import duties.15 The more successful traders continued to move apparel from China, the United Arab Emirates, and especially Turkey, with the assistance of freight companies specializing in cargo delivery to their specific cities, including Moscow, Khabarovsk, Kishinev, or Almaty (Aktar and Ögelman 1994;Zhurzhenko 1999).This history of post-Soviet mobility forms a critical part of the backdrop to the experience of many post-Soviet border crossers, including shuttle traders like Zhenia, whose mobility inserted them into a global economy and required them to engage with new intimate economies but also with rapidly shifting border regimes.Although this situation is not unlike those described by scholars writing about migrant women in Japan (Faier 2009) or South Korea (Cheng 2010), in the case of migrant women from the former Soviet Union, gender ideals, mobility, and intimate practices come together in distinctive ways.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".