MétaCan
Menu
Back to cohort
Record W4285464960 · doi:10.32920/ryerson.14637000.v1

Newcomer Services in the Greater Toronto Area: an Exploration of the Range and Funding Sources of Settlement Services

2021· preprint· en· W4285464960 on OpenAlexaboutno aff
April Lim, Lucia Lo, Myer Siemiatycki, Michael Doucet

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationSettlement (finance)Agency (philosophy)Service (business)Government (linguistics)Public administrationBusinessPolitical scienceLibrary scienceSociologyFinanceMarketingLawSocial scienceComputer science

Abstract

fetched live from OpenAlex

<p>This paper provides a profile of newcomer services and the agencies which provide them to recent immigrants in the Greater Toronto Area (GTA). It is intended as a resource for researchers, immigrants, agency, community and government organizations. The paper begins by reviewing: the range of newcomer services available, trends in recent immigrant settlement in the Toronto area, and a description of funding sources for newcomer services in the GTA. Next we discuss our research methodology and identify some limitations to the material we present. The bulk of the paper consists of an identification of agencies providing newcomer services in the City of Toronto and RegionalMunicipalities of Durham, Halton, Peel and York. We cite location, funding source(s), and program offering(s) foreach agency. The paper concludes with tabulated summaries of the agencies described.</p><br><p>KEY WORDS: newcomer services; immigrant service agencies; Toronto immigration settlement; newcomer service funding</p><div><br></div>

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.062
GPT teacher head0.320
Teacher spread0.258 · 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 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

Citations30
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicMigration and Labor DynamicsFrench-language works237,207