MétaCan
Menu
Back to cohort
Record W2120096368 · doi:10.1525/can.2005.20.4.534

Longing for the Kollektiv: Gender, Power, and Residential Schools in Central Siberia

2005· article· en· W2120096368 on OpenAlexaff
Alexia Bloch

Bibliographic record

VenueCultural Anthropology · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Reforms and Inequalities
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPower (physics)SociologyGender studiesDemography

Abstract

fetched live from OpenAlex

Interpretations of post-Soviet subjectivities have tended to emphasize the ways in which subjects experience these with a sense of liberation from a monolithic socialist state; however, local responses to post-Soviet forms of power have varied widely. In the case of indigenous Siberians in the 1990s, an older generation of Evenk women expressed positive feelings about their experience as students in the Soviet-era residential schools that continue to shape their subjectivity in the post-Soviet present. Evenk subjectivities, as with those of other indigenous Siberians, have been significantly formed through the institution of the residential school and, by extension, through a range of interactions with state power as it has been locally remade and interpreted in the 1990s. In this article, I explore the widespread nostalgia associated with the residential school. Drawing on the narratives of elderly Evenk women, I argue that such expressions of Evenk nostalgia for the socialist era are a form of critique of the neoliberal logics emerging in Russia today. In this respect, Evenk women's accounts allow us to explore negotiations of power in a post-Soviet era and to examine how ideologies shape conceptions of self and the social order more broadly.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.010
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.050
GPT teacher head0.392
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCultural AnthropologySame topicGlobal Educational Reforms and InequalitiesFrench-language works237,207