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Record W7064679161

Community Ideas Factory: The Life Skills Project

2024· article· en· W7064679161 on OpenAlexaboutno aff

Bibliographic record

VenueSOURCE Sheridan's Institutional Repository (Sheridan College) · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsnot available
Fundersnot available
KeywordsLife skillsSkills managementResearch councilSocial skillsSocial lifeFactory (object-oriented programming)Lifelong learningKey (lock)
DOInot available

Abstract

fetched live from OpenAlex

This is the third Community Ideas Factory initiative – ‘The Life Skills project’, a collaborative social innovation research project that originated at Sheridan College and is funded through the College and Community Social Innovation Fund, which is managed by the Natural Sciences and Engineering Research Council of Canada (NSERC) in collaboration with the Canadian Institutes of Health Research (CIHR) and the Social Sciences Humanities Research Council of Canada (SSHRC). This is a 3-year research project which proposed an innovative response to the need for effective life skills programming. This social innovation is a comprehensive, lived- experience and EDI-informed, life skills program that includes several key topic areas (modules) and associated interactive applications which allows the learner to practice the skills being taught in a virtual setting to prevent homelessness. The project resulted in a virtual Learning Management System (LMS).

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)0.017
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.037
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.003
Scholarly communication0.0060.003
Open science0.0020.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0370.008

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 head0.015
GPT teacher head0.273
Teacher spread0.257 · 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
Published2024
Admission routes1
Has abstractyes

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