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Record W7105524223 · doi:10.5281/zenodo.16923488

Harvest for the Heart: Cardiometabolic Disorder 2026 Health Literacy Summit

2025· article· W7105524223 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsSummitExhibitionNarrativeTimelineIdentity (music)HonorCornerstonePersonal narrative

Abstract

fetched live from OpenAlex

2026 Health Literacy Collaborative Summit R&D HX Entry: Cultural Catalyst For years, we envisioned CultureCare.online as a platform that fuses heritage, art, and wellness — a living archive where Black artistry and intergenerational narratives are not only preserved but centered. This article crystallized the urgency of moving forward with our long-planned goals. It confirmed something we’ve known intuitively: when institutional spaces overlook Black creativity, our homes, gardens, and digital spaces become the galleries. Re-imaging my own space within common community spaces—not just as decor, but as a place where values, identity, and vision live. It’s a call to curate life on my own terms and to honor narratives often overlooked. Key Insights from the Article Homes as Living Archives → Historically, Black collectors transformed personal spaces into sanctuaries of culture because traditional art institutions excluded their narratives. Gaps in Representation → Between 2008 and 2020, only 2.2% of U.S. museum exhibitions and 0.5% of acquisitions featured work by Black American women. Personal Curatorship → Collectors like Kenneth Montague, Aurora James, Kimberly Drew, and Malene Barnett embody what it means to claim space, curate legacy, and uplift community by making art part of daily life. Intergenerational Impact → Black collecting traditions serve as pathways to storytelling, healing, and reclaiming identity for future generations. HX Reflection This moment marks a turning point: we’re no longer dreaming, we’re documenting. Inspired by the collectors featured here, we’re advancing our initiatives — from the Cornerstone Cherubs Heritage Collection to Soul 2 Soil’s cultural archiving efforts. Our work will position personal archives, gardens, and homes as active heritage sites, where art and memory live alongside health, sustainability, and collective identity. Moving Forward This HX entry ties directly into: Cornerstone Cherubs Heritage Collection → expanding the archive of visual and digital storytelling. Soul 2 Soil Project → weaving together heritage gardening, environmental stewardship, and artistic preservation. Culturecare.online → amplifying Black cultural expression while creating self-sustaining models of wellness, art, and narrative ownership. Digital Template: © 2025 Tiffany T Johnson Source: Architectural Digest (Feb 21, 2025) Link: Collector Highlights: Dr. Kenneth Montague – Wedge Gallery became a community platform in Toronto. Aurora James – integrates her designer identity and values into her living space. Kimberly Drew – art collection as intimate, cultural sustenance. Malene Barnett – her home is both gallery and archive, challenging institutional hierarchies. *Researcher Alignment Note* This record documents the intersection of culture, health literacy, and equity through narrative and archival practices. While not a clinical dataset, it aligns with researcher expectations by providing transparent methodology, open licensing, and evidence‑based framing. Scholars in health equity, cultural studies, and narrative medicine will find the work relevant as a qualitative reflection and advocacy resource. Future versions will continue to integrate citations, context notes, and engagement metrics to strengthen reproducibility and scholarly value.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.083
Threshold uncertainty score0.279

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0050.002
Open science0.0010.009
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0830.025

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 head0.057
GPT teacher head0.393
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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