MétaCan
Menu
Back to cohort
Record W2765703189 · doi:10.1111/glob.12174

Sent home: mapping the absent child into migration through polymedia

2017· article· en· W2765703189 on OpenAlexfundno aff
Deirdre McKay

Bibliographic record

VenueGlobal Networks · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaKeele UniversityArts and Humanities Research CouncilBritish Academy
KeywordsAbandonment (legal)VisibilityRaising (metalworking)SociologyGender studiesPolitical scienceDevelopmental psychologyPsychologyGeographyLaw

Abstract

fetched live from OpenAlex

Abstract Migrants and their transnational families document their children and child‐rearing practices on social networking sites (SNS) to enhance their social mobility. In this article, I identify a new group of migrant children, namely those sent home to their parents’ countries of origin for an imagined ‘good childhood‘. I demonstrate that polymedia – SNS and other platforms – sustain these children and create new norms of publicness and visibility in transnational parenting. Exploring how families document child‐raising across international boundaries, I show how the trajectories of parenting relationships remain open ended. I counter the predominant focus on transnational parenting as a kind of abandonment attached to left‐behind children. Instead, I refocus the research on the opportunities polymedia give families to create and sustain intimacies, thus making the trajectories of migrant families and children increasingly dynamic. Polymedia create important shifts in global migration – a transformation that requires changes in the way scholars approach transnational families and long‐distance parenting.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.020
GPT teacher head0.293
Teacher spread0.274 · 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 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

Citations12
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueGlobal NetworksSame topicMigration and Labor DynamicsFrench-language works237,207