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Record W4285740004 · doi:10.18260/1-2--39258

SETT: A Framework for Capacity Building Partnerships

2024· article· en· W4285740004 on OpenAlexaff
Laurene Sweet, Alisa Jones, Colin K. Drummond

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsLethbridge College
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institutes of Health
KeywordsComputer scienceArchitectural engineeringEngineering

Abstract

fetched live from OpenAlex

A contemporary issue for many non-profits is identifying effective ways to build capacity for service delivery. Interdisciplinary processes take time to carry out; herein lies a challenge when working with a university in which the lifecycle of student activity is not aligned (much shorter) that of the project for the alternative education program. In the current work, we describe the pathway of a partnership that improves the ability of nonprofit staff to achieve their mission while simultaneously meeting the service motivation in an academic setting. This paper describes the "pathway" for a mutually beneficial collaborative relationship between a higher education institution and a non-profit serving students with moderate to severe disabilities for the development of Assistive Technology using the SETT Framework as well as the Stanford BioDesign process.

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.795
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.332
GPT teacher head0.516
Teacher spread0.184 · 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
GenreMethods

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

Citations1
Published2024
Admission routes1
Has abstractyes

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