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Record W4309938159 · doi:10.1080/00085006.2022.2135357

Security through emotions: narratives of temporal and spatial belongings of the Polish Territorial Defence Forces

2022· article· en· W4309938159 on OpenAlexvenueno aff
Bettina Bruns

Bibliographic record

VenueCanadian Slavonic Papers · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsnot available
FundersVolkswagen Foundation
KeywordsNarrativePolitical scienceHistoryPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Since Russia’s annexation of Crimea, militarization processes have started to take place in central and eastern Europe. In Poland, one element of this development is the establishment of Territorial Defence Forces (TDF) in 2017. They are assigned to support their local communities, to strengthen patriotism, and to provide a feeling of security among the local population. Drawing from official websites and social media accounts of TDF as well as from national security policy documents, this article examines the role of emotions with regard to the TDF’s task as security provider. By combining literature on emotions and narratives of belonging with security conceptions, the article argues that TDF contribute to security less through their military strength than through the spatial and temporal belongings they offer publicly. Spatial narratives of belonging contain emotions of love and affection towards home regions and the state with the aim of translating them into territorialized security practices. Temporal narratives of belonging refer to the Home Army and “cursed soldiers,” revealing strong emotional attachments to armed resistance and thereby providing a role model for contemporary security production. Simultaneously, TDF express their non-belonging to the socialist past as a further element to produce security.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2022
Admission routes1
Has abstractyes

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