MétaCan
Menu
Back to cohort
Record W2125637422 · doi:10.1177/146144804044327

New ties, old ties and lost ties: the use of the internet in diaspora

2004· article· en· W2125637422 on OpenAlexaffabout
Harry H. Hiller, Tara M. Franz

Bibliographic record

VenueNew Media & Society · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Calgary
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsDiasporaInterpersonal tiesHomelandCyberspaceThe InternetStrong tiesIdentity (music)Social capitalSociologyImmigrationInternet usersPolitical scienceSocial psychologyGender studiesPsychologyWorld Wide WebLawSocial scienceComputer science

Abstract

fetched live from OpenAlex

The computer represents a new resource in developing social capital that previously did not exist among migrants. The relationship between physical space and cyberspace is discussed using the experience of migrants from Newfoundland who, although dispersed from their homeland, use the computer to maintain ties with both their homeland and others in diaspora. Three phases in the migration cycle are identified (pre-migrant, post-migrant, settled migrant) and four categories of computer usage are linked to each phase. Three types of online relationships can be identified among diasporic peoples that result in developing new ties, nourishing old ties and rediscovering lost ties. The processes of verification, telepresence, hyperreality and attribution are discovered and illustrated from online data and interviews which indicate how computermediated communication is related to both social networking and identity among migrants.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0040.004
Open science0.0000.004
Research integrity0.0010.001
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 head0.060
GPT teacher head0.285
Teacher spread0.225 · 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

Citations302
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueNew Media & SocietySame topicSocial Media and PoliticsFrench-language works237,207