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Record W2516491507 · doi:10.3138/tric.37.1.92

Investigating <i>Afghanada</i>: Situating the CBC Radio Drama in the Context and Politics of Canada and the War on Terror

2016· article· en· W2516491507 on OpenAlexvenueaboutno aff
Lindsay Thistle

Bibliographic record

VenueTheatre Research in Canada · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsDramaPoliticsContext (archaeology)GlobeMedia studiesSpanish Civil WarTerrorismSociologyHistoryAestheticsPolitical scienceLiteratureLawPsychologyArt

Abstract

fetched live from OpenAlex

In 2008, Globe and Mail theatre critic J. Kelly Nestruck made a significant remark about Canadian theatre and the War on Terror, noting a clear absence of stage plays that addressed Canada’s participation. There was, however, a long-running CBC radio drama series, Afghanada, which centred fully on the experiences of Canadian soldiers in Afghanistan. Because relatively little research has yet to be published about the radio series, Lindsay Thistle details Afghanada’s production history, major players, creative processes and goals. She also considers how the radio medium affected the objectives of the series and its ability to represent war, ultimately arguing that Afghanada was inescapably politicized throughitsrelationship with national institutions, its interest in realistic and true-to-life stories, its focus on everyday soldiers, its casting choices and its inclusion of post-traumatic stress disorder. Throughout this investigation, Thistle raises important questions about the politics of dramatizing war while Canada itself was at war. She concludes by observing that while Afghanada avoids an explicit message in support of or against the Canada’s involvement in the War on Terror, it engaged with the political from its inception, through its creation, and in its reception.

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)0.005
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.051
GPT teacher head0.311
Teacher spread0.260 · 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 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

Citations0
Published2016
Admission routes2
Has abstractyes

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