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Record W2023938150 · doi:10.1017/s1049096513000176

Teaching the “New Middle East”: Beyond Authoritarianism

2013· article· en· W2023938150 on OpenAlexaff
Khalid Mustafa Medani

Bibliographic record

VenuePS Political Science & Politics · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsAuthoritarianismMiddle EastScholarshipPoliticsDemocracyPolitical scienceState (computer science)Political economyWitnessCivil societyDevelopment economicsSociologyLawEconomics

Abstract

fetched live from OpenAlex

In 2011 the protests in the Middle East and North Africa (MENA) were not only unprecedented in terms of scale and political consequences for the region, they also highlighted a number of long-standing analytical and theoretical misconceptions about Arab politics. In particular, the conventional thesis privileging the idea of a “durable authoritarianism” in the Arab world was partially undermined by a cross-regional civil society that confronted the formidable security and military apparatus of the state. Although in some countries democratic transitions have continued, since they first occurred in Tunisia, other Arab states continue to witness a resilient authoritarianism and strong state repression of civil society activism. These historic events have also set the stage for a new teaching agenda in important ways. Specifically, an agenda for teaching the “new Middle East” must incorporate two important general components: first, a critical review of the influential scholarship on persistent authoritarianism with the objective of addressing past theoretical and methodological misconceptions, and second, the introduction of new conceptual and analytical frameworks relevant to contemporary political developments in the Arab world and the MENA region more generally.

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)0.007
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.007
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.023
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.318
Teacher spread0.269 · 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 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

Citations3
Published2013
Admission routes1
Has abstractyes

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