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Peoples’ Uprising in North Africa and Middle East: Lessons Learnt and Challenges of Policy Implication-Egypt as an Illustrative Case

2012· article· en· W1894752324 on OpenAlexvenueno aff
Harold Sougato Baroi

Bibliographic record

VenueCanadian social science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsMiddle EastContext (archaeology)Political scienceHumanitiesHistoryLawArt

Abstract

fetched live from OpenAlex

A revolutionary wave that began in Tunisia fi rst and then moved from Egypt to Libya, Bahrain, Syria, Yemen, Morocco, Lebanon, Oman and other countries in the Arab world was perhaps the most discussed issue in 2011. Years of frustration vented out when people in most of the Arab countries came on the streets, demanding change. This particular article is an attempt to understand what made these people involved in such revolution and how these factors have an impact on policy implication from a change perspective. The study required extensive research and attempts have been made to make best use of existing literatures and secondary sources of information like newspapers, interviews at various news channels, online journals and blogs. Here in the article, Egypt has been taken as a case to narrow down the focus on one particular country taking into account the overall essence of the entire region and similarity in the context. Moreover considering the time and resource factors involved in this kind of work, was also considered while selecting a single case in order to come up with logical conclusions. Key words : People’s uprising; Arab spring; Confl ict; Policy implication; Do No Harm Resume Une vague revolutionnaire qui a commence en Tunisie d’abord et ensuite de l’Egypte a la Libye, Bahrein, Syrie, Yemen, Maroc, Liban, Oman et d’autres pays dans le monde arabe etait peut-etre la question la plus discutee en 2011. Des annees de frustration evacuee quand les gens dans la plupart des pays arabes sont venus dans les rues, exigeant le changement. Cet article en particulier est une tentative de comprendre ce qui a fait ces personnes impliquees dans cette revolution et comment ces facteurs ont une incidence sur l’implication politique dans une perspective de changement. L’etude a necessite des recherches approfondies et des tentatives ont ete faites pour faire le meilleur usage de la litterature existante et des sources secondaires d'information comme les journaux, des interviews a divers canaux d'information, en ligne des revues et des blogs. Ici, dans l’article, l’Egypte a ete prise comme un cas a affi ner la mise au point sur un pays en particulier en tenant compte de l’essence globale de toute la region et de la similarite dans le contexte. Par ailleurs compte tenu du temps et de facteurs lies aux ressources impliquees dans ce genre de travail, a egalement ete examinee lors de la selection d’un seul cas en vue d’arriver a des conclusions logiques. Mots cles : Soulevement populaire; Printemps arabe; Les confl its; Implication politique; Do No Harm

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.117
GPT teacher head0.335
Teacher spread0.218 · 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 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

Citations9
Published2012
Admission routes1
Has abstractyes

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