MétaCan
Menu
Back to cohort
Record W2914839742 · doi:10.7176/nmmc.vol7711-16

The Impact of Media on Mobility: The Case of Ethiopian Migrants in the West

2019· article· en· W2914839742 on OpenAlexaboutno aff
Samuel Mochona Gabore

Bibliographic record

VenueJournals & Books Hosting (International Knowledge Sharing Platform) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsDiasporaSocial mediaPersecutionPoliticsGeographyPolitical scienceMedia useConsumption (sociology)Media consumptionDemographic economicsDevelopment economicsAdvertisingBusinessSociologySocial scienceEconomicsPsychologyLaw

Abstract

fetched live from OpenAlex

As a recent phenomenon, increasing number of Ethiopians are leaving their country and trying to reach the West. The pull and push factors range from expecting better opportunities in the destination to fleeing political persecution. Combining survey data from Ethiopian Diaspora with information from international and national migration organizations, this study explores which media play key roles in migration of people. Over the period of 15 years, from 2000 to 2014, a steadily increasing number of Ethiopians have been migrated to countries such as United States, Canada, Germany, Israel, Norway and Sweden. These countries are either broadcasting traditional media to Ethiopia or having strong Ethiopian social media networks. In making migration decisions, consumption of Western media and prior existence of networks play crucial roles. There has been constant or increasing number of migration to the countries which transmit media, radio and television, particularly in Ethiopian languages and where there are large numbers of Ethiopian Diasporas. In addition, social media is playing important roles in facilitating migration by creating and maintaining networks (connectivity) and providing information. Matchmaking sites are also contributing significantly by creating connectivity that eventually leads to marriage migration. DOI : 10.7176/NMMC/77-02

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.074
GPT teacher head0.396
Teacher spread0.322 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournals & Books Hosting (International Knowledge Sharing Platform)Same topicDiaspora, migration, transnational identityFrench-language works237,207