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Record W4396581055 · doi:10.1111/imig.13261

Searching for settlement information on Reddit

2024· article· en· W4396581055 on OpenAlexafffundabout
Stein Monteiro

Bibliographic record

VenueInternational Migration · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsToronto Metropolitan UniversityConference Board of Canada
FundersCanada Excellence Research Chairs, Government of CanadaGovernment of Canada
KeywordsSettlement (finance)Service (business)Scope (computer science)Service providerPublic relationsBusinessSociologyComputer scienceWorld Wide WebPolitical scienceMarketing

Abstract

fetched live from OpenAlex

Abstract Newcomers are using informal means to find settlement information that is also freely available through formal settlement service providers. Newcomers may seek settlement information on Reddit when the same information might be found through a settlement service provider. This study finds that several Reddit submissions can be categorized in at least one or more of the formal settlement service categories. There is some overlap between informal conversations on Reddit and formalized settlement services. However, informal spaces go beyond providing settlement information in formalized categories. These results suggest that there is scope for policymakers to take a closer look at online conversations to better understand the needs of newcomers when they are looking for information about settling in Canada before and after they arrive. There is the potential to use this information to identify service gaps and create new funded settlement service categories. There is also the potential to accurately train a machine learning model to classify new Reddit submissions and produce real‐time advice to policymakers on newcomer information needs.

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 score0.946
Threshold uncertainty score0.214

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)0.0000.000

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 head0.033
GPT teacher head0.393
Teacher spread0.360 · 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

Citations9
Published2024
Admission routes3
Has abstractyes

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