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Record W4402773842 · doi:10.4324/9781003519522

Masculinities and Queer Perspectives in Transitional Justice

2024· book· en· W4402773842 on OpenAlexfundno aff
Philipp Schulz, Brandon Hamber, Heleen Touquet

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaEnvironment and Climate Change CanadaKroc Institute for International Peace Studies, University of Notre DameUniversidad de los AndesAfrican UnionUnited NationsBundesministerium für Bildung und ForschungUniversity of CambridgeEuropean CommissionAlexander von Humboldt-Stiftung
KeywordsQueerTransitional justiceGender studiesSociologyEconomic JusticePolitical scienceCriminologyLaw

Abstract

fetched live from OpenAlex

A generation after the end of the Croatian War of Independence, transitional justice advocates had hoped Croatian society would be able to separate individual and organizational responsibility for war crimes from the moral significance of a war of self-defense. Instead, young people’s entire lives as students, citizens, and family members have been lived amid the continued predominance of what Dejan Jović has termed a congratulatory and uncritical “myth of the Homeland War” and amid extended economic precarity. The much-mythologized generation of wartime soldiers, or “branitelji” (“defenders”), has meanwhile become middle-aged veterans with material vulnerabilities of their own. The media’s ongoing production of “veteran” masculinities, made meaningful to youth in domains including sport and popular music, as well as official commemoration, affirms the dominant public narrative of the Homeland War in Croatia. The phenomenon also suggests that, where transitional justice processes are still salient a generation after conflict, understanding the relationship between masculinities and transitional justice requires attention to how age- and conflict-related masculinities interact.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.692
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.041
GPT teacher head0.226
Teacher spread0.185 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations6
Published2024
Admission routes1
Has abstractyes

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