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Record W4247316959 · doi:10.32920/ryerson.14647284

It's all about needs: the role of Christian congregations in addressing the social exclusion barriers of seasonal agricultural workers

2021· preprint· en· W4247316959 on OpenAlexaffabout
Carissa Groot-Nibbelink

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSettlement (finance)Social exclusionSocial workAgricultureSociologyInclusion (mineral)Work (physics)Service (business)Social WelfarePublic relationsSpecial needsFace (sociological concept)Political scienceGeographyBusinessSocial sciencePsychologyMarketingEngineeringArchaeologyFinanceLaw

Abstract

fetched live from OpenAlex

This paper examines the role of Christian congregations in addressing the social exclusion barriers experienced by seasonal agricultural workers (SAWs). This research study reviews the ways in which local churches support SAWs specifically in the Niagara Region. This paper also examines the benefits and limitations of this support and thus offers recommendations to enhance the future work of congregations in this area. This study reveals the evolving role of Christian congregations from offering only fellowship and spiritual services to SAWs to responding to their true needs in areas such as transportation, health care, language, and social inclusion. Because SAWs continue to face significant social exclusion barriers and still remain ineligible for settlement services in Ontario, it is important that congregations continue to do this work, meeting the needs of SAWs and growing in their ability as social service providers. Key words: seasonal agricultural workers (SAWs), congregations, Christian, the Niagara Region, social services, settlement support, social exclusion, 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 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)0.002
metaresearch head score (Gemma)0.004
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 score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.004
Scholarly communication0.0020.001
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.257
Teacher spread0.231 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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