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Record W2229833717

ICT and Migration: A Conceptual Framework of ICT Use by Migrants

2012· article· en· W2229833717 on OpenAlexaff
Simon Collin, Thierry Karsenti

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsInformation and Communications TechnologyConceptual frameworkSituatedMigration studiesSociologyEconomic geographyPolitical scienceRegional scienceEconomic growthGeographySocial scienceGender studiesEconomics
DOInot available

Abstract

fetched live from OpenAlex

International migration has steadily increased to become a significant trend. ICT have had a major impact on it, giving rise to a new age of “connected migrants”. Drawing from the emerging field of ICT and migration, this paper explores the use of ICT by migrants. Based on a literature review, it presents a conceptual framework of ICT use by migrants throughout the migration process. The framework includes four main components, situated along two axes: the “host society – source society” and the “pre-migratory phase – post-migratory phase” axis. We conclude with some avenues for future research. ICT and migration research area International migration has steadily increased to become a significant trend in Western societies (Massez, Arango, Hugo, Kouaouci, Pelligrino & Taylor, 1993), stirring scientific interest. For example, Urry (2010) urges sociology to reframe its perspectives by moving from the “social as society” to the “social as mobility” (p. 348); which he calls “mobile sociology”, highlighting the attention that is given to migration, as a growing social trend. Currently, an estimated 215 million people are on the move (World Bank, 2011), for an 11 % rise on average from 2002 to 2007 (Organization for Economic Cooperation and Development, OECD, 2010). ICT have certainly had a major impact on the entire process of mobility and migration (Codagnone & Kluzer, 2011). In his conceptual study, Kellerman (2011) concludes that all current mobilities are based on and dependent on ICT. Whence the emerging research on ICT and migration, it is recognized that ICT have had a major impact on migration trends by considerably diversifying and increasing migration opportunities (Codagnone & Kluzer, 2011; Hamel, 2009). ICT have also helped change our conception of migrants. According to Diminescu (2005), migrants have traditionally been perceived as uprooted individuals who must overcome a series of breaks with the past. However, the new image is that of connected individuals (the “connected migrants”) whose mobilities are parts of a continuum. This new perception is made possible by ICT, which allow us to develop an “inclusive cosmopolitan point of view ‘both here and there’, rather than an exclusive vision based on “neither... or’” (free translation, Nedelcu, 2009, p. 171). This contrasts with the view of the migrants as lacking, torn between two realities and never truly belonging to either one (Sayad, 1999). Although ICT and migration is a recent research area (Codagnone & Kluzer, 2011), it has generated growing interest (Borkert, Cingolani & Premazzi, 2009) and is an emerging research stream. A multidisciplinary topic, it involves a diverse mix of expertise, approaches and purposes. Some studies focus on defining, conceptualizing and delineating the field (e.g., Borkert, Cingolani & Premazzi, 2009; Diminescu, Jacomy & Renault, 2010). Our study belongs in this theoretical stream. Objective and methodology Our aim was to contribute to the collective reflection on ICT and migration by identifying ICT use by migrants. We drew our portrait of ICT and migration based on a literature review using the methodology proposed by Gall (2005) and Fraenkel and Wallen (2003). Thus, we began by formulating a research question for the literature review: How are ICT used by migrants throughout the migration process? We then determined key words: ICT + migrants/migration + uses. We searched for key words combinations in general online databases (e.g., Google, Google Scholar) and specialized websites on this question (e.g., section “State of the art” section of the

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.305
Teacher spread0.279 · 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 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

Citations10
Published2012
Admission routes1
Has abstractyes

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