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Record W1537803647 · doi:10.1007/978-94-6209-233-4_2

Volunteer Work and Informal Learning

2013· book-chapter· en· W1537803647 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSensePublishers eBooks · 2013
Typebook-chapter
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of AlbertaCanadian Co-operative Association
Fundersnot available
KeywordsInformal learningWork (physics)Volunteer workInformal educationDynamics (music)SociologyPublic relationsPedagogyPolitical scienceEngineeringHigher educationLaw

Abstract

fetched live from OpenAlex

Informal learning and volunteer work are two dynamics that coexist everyday in communities throughout the world. However, we still know comparatively little about the nature of these dynamics. While an abundant literature exists on work, only a small portion of this literature deals with volunteer work. Likewise, only a minority of the vast literature on learning explores dynamics of informal learning. In the same way that volunteer work has a marginal place in the study of work; informal learning has a marginal place in the literature on learning. The chapters included in this book deal explicitly with the learning dimension of volunteer work, a topic that has not yet attracted the interest of many researchers. Nonetheless, we suggest that the topic is important because, as we will argue in the following pages, both volunteer work and informal learning are present in our daily lives and necessary for the reproduction of our daily lives.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.240
Teacher spread0.214 · 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