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Record W4400406167 · doi:10.1080/10790268.2024.2369736

Priorities and opportunities for advocacy in SCI: An international web-based review

2024· review· en· W4400406167 on OpenAlexaff
Vyshnavi Manohara, Anna Nuechterlein, Tanya A. Barretto, Judy Illes

Bibliographic record

VenueJournal of Spinal Cord Medicine · 2024
Typereview
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsNeuroDevNetUniversity of British Columbia
Fundersnot available
KeywordsPolitical scienceWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

CONTEXT: For the growing number of people with spinal cord injuries worldwide, advocacy organizations are an invaluable resource of information and education during recovery and rehabilitation. OBJECTIVE: To examine the structure, information, and accessibility of websites from international organizations that serve and advocate for individuals with SCI. METHODS: We performed a content analysis of information available from SCI organizations returned from a Google search. We used search terms relevant to SCI and advocacy and applied them to top-level domains for the G20 countries. Organizations that provide services or advocate for people with SCI with English-language websites were included; organizations focused on research, fundraising, clinical care, interprofessional knowledge exchange, or other neurological conditions were excluded. Accessibility, in terms of ease of use to information about participation, was assessed using a 3-point scale. RESULTS: = 11). Across these, six categories of resources and services are covered: (1) education, (2) physical health, (3) external, (4) peer support, (5) mental health, and (6) financial and legal. Eleven organizations indicate specific engagement with research or clinical trials. Four websites provided highly accessible information (rank = 3) about participation in research. CONCLUSION: The SCI organizations identified in this study offer resources that largely pertain to education and physical health services and strategies. Information about clinical trials and SCI research studies are easily accessible on the websites of the limited number of organizations offering avenues for participation.

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)0.013
metaresearch head score (Gemma)0.037
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0160.017
Science and technology studies0.0010.001
Scholarly communication0.0050.007
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.365
GPT teacher head0.541
Teacher spread0.175 · 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
GenreReview

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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