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Record W2399309201 · doi:10.20355/c5588n

Young People’s Response to The Response: The Impact of Political Diversity and Media Framing on Discussions of Combatant Tribunals

2016· article· en· W2399309201 on OpenAlexvenueno aff
Jeremy Stoddard, Jason Chen

Bibliographic record

VenueJournal of Contemporary Issues in Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCombatantFraming (construction)PoliticsPolitical sciencePolitical efficacySociologySocial psychologyLawPsychologyHistory

Abstract

fetched live from OpenAlex

This article presents results of a study of the impact of political dynamics on group deliberations of issues presented in the short film The Response. We selected four groups of 18-22 year-old participants based on political views, engagement, and efficacy (liberal, conservative, and two mixed groups), and asked them to view and discuss issues presented in The Response related to the combatant status review tribunals held at Guantanamo Bay. We found the groups with mixed political views had higher quality discussions of the issues and a better understanding of the issues post-discussion – in particular the tension between national security versus individual rights and of the nature of the tribunals. We also found a significant number of conservative group members became more conservative in their views as a result of their discussion. We discuss implications for secondary and post-secondary education as well as for political polarization overall in society.

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)0.011
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.003
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.084
GPT teacher head0.428
Teacher spread0.344 · 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 designObservational
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

Citations1
Published2016
Admission routes1
Has abstractyes

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