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Record W4312799511 · doi:10.15406/ijfcm.2022.06.00274

People with disabilities family: highlighting an ancestral knowledge to guarantee food security

2022· article· en· W4312799511 on OpenAlexaff
Nina Madrigal Zuluaga, Diana Carolina Perez Torres, Sebastián Ardila Osorio, Daniel Emilio Castrillón Builes, Diana Rocío Mina Mina

Bibliographic record

VenueInternational Journal of Family & Community Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicAging, Health, and Disability
Canadian institutionsImpact
Fundersnot available
KeywordsDiversity (politics)Food securityWork (physics)RehabilitationSample (material)SociologyPublic relationsPsychologyGeographyPolitical scienceEngineeringAgriculture

Abstract

fetched live from OpenAlex

The following article describes the research carried out during 2020 in Santander de Quilichao, Cauca of the project called "Family Gardens for Santander de Quilichao" whose lines of work focused on food security and community strengthening in families with children with disabilities; through the implementation of community gardens and training for parents, addressing disability as a sample of human diversity. The project yielded positive results, having as a methodological reference the Community-Based Rehabilitation strategy; directly benefiting 45 families and 150 people, with a total of 30 urban gardens and 2 home gardens. The research carried out shows how community development can be approached holistically, taking up elements of the community; thus facilitating access to and participation of persons with disabilities.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.004
Scholarly communication0.0020.002
Open science0.0000.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.082
GPT teacher head0.375
Teacher spread0.293 · 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 designObservational
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
Published2022
Admission routes1
Has abstractyes

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