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Record W4304989902 · doi:10.1136/bmjopen-2022-060952

Food insecurity among postsecondary international students: a scoping review protocol

2022· review· en· W4304989902 on OpenAlexaff
Jonathan Amoyaw, Mamata Pandey, Geoffrey Maina, Yiyan Li, Daniel Owusu Nkrumah

Bibliographic record

VenueBMJ Open · 2022
Typereview
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsCanadian Light Source (Canada)Saskatchewan Health AuthorityPrince Albert Grand CouncilUniversity of SaskatchewanSaskatchewan HealthDalhousie University
Fundersnot available
KeywordsMedicineProtocol (science)Food insecurityEnvironmental healthPublic healthMedical educationAlternative medicineNursingFood securityPathology

Abstract

fetched live from OpenAlex

Introduction International students make significant contributions to their host institutions and countries. Yet research shows that not all international students have the financial means to fend for themselves and meet their financial obligations for the entire study programme. Such students are at significant risk of food insecurity. The objective of this scoping review is to synthesise available information on the factors related to food insecurity among international students studying at postsecondary educational institutions and identify the types of food insecurity interventions that have been implemented to address this issue. Methods and analysis The Joanna Briggs Institute scoping review methodology will be used to guide this scoping review, and we will search the following databases: MEDLINE (through Ovid), CINAHL (EBSCO), PubMed, ERIC (via Ovid), PROSPERO and ProQuest. The titles, abstracts, and subsequently full texts of the selected papers will then be screened against the inclusion criteria. Data from articles included in the review will be extracted using a data charting form and will be summarised in a tabular form. Thematic analysis will be used to identify common themes that thread through the selected studies and will be guided by the steps developed by Terryet al. Ethics and dissemination Since this project entails a review of available literature, ethical approval is not required. The findings will be presented at academic conferences and published in a peer-reviewed journal. To make the findings more accessible, they will also be distributed via digital communication platforms.

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)0.129
metaresearch head score (Gemma)0.089
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.129
Threshold uncertainty score0.684

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1290.089
Meta-epidemiology (narrow)0.0050.007
Meta-epidemiology (broad)0.0130.010
Bibliometrics0.0180.013
Science and technology studies0.0050.006
Scholarly communication0.0080.009
Open science0.0060.006
Research integrity0.0100.007
Insufficient payload (model declined to judge)0.0670.018

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 head0.589
GPT teacher head0.680
Teacher spread0.091 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations13
Published2022
Admission routes1
Has abstractyes

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