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Record W4405975979 · doi:10.1093/geroni/igae098.1088

THE GLOBAL PRIDE STUDY: LESSONS LEARNED AND NEXT STEPS

2024· article· en· W4405975979 on OpenAlexaff
Karen I. Fredriksen‐Goldsen, Christi Nelson, Austin Oswald, Hyun‐Jun Kim

Bibliographic record

VenueInnovation in Aging · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPrideComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract As the older adult population becomes increasingly diverse and globalized, new challenges emerge in gerontological research and practice worldwide. This presentation examines sexuality, gender, and aging within a global context, exploring both fortitude and risks, as well as differing social and cultural interpretation of sexuality, gender, and age in relation to research and the development of culturally relevant practices. We will discuss the formation of the research network, involving more than 50 international collaborators. As part of the Global Pride project, we developed and tested a pilot survey, which was distributed by 18 partners and completed across six global regions (N= 3,885). Key processes and lessons learned include: 1. Establishing an international network of researchers to exchange knowledge and experiences in studying sexuality, gender, longevity, and health holistically; 2. Implementing a collaboratively developed survey across six global regions, taking into consideration differing cultural contexts and methodologies; 3. Employing culturally tailored dissemination strategies across diverse regions and settings. The insights gleaned from this research will deepen an awareness of the diversity of lives across the life course and contribute knowledge about the richness, challenges, and heterogeneity of ageing, as well as best practices for the implementation of global research.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.165
GPT teacher head0.368
Teacher spread0.203 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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