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Record W2493908509 · doi:10.1007/978-1-137-56994-3_7

Contributions to Community and Organization

2015· book-chapter· en· W2493908509 on OpenAlexaff
Robert A. Stebbins

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2015
Typebook-chapter
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGrassrootsGenerosityCasualSocial capitalSocial organizationCommunity organizationPublic relationsSociologyCivil societyCommunity organizingAltruism (biology)Social activismInterpersonal tiesPolitical scienceSocial psychologyPsychologySocial scienceLaw

Abstract

fetched live from OpenAlex

When it comes to contributions to community and organization, generosity is the principal emotion. Altruism is also strongly felt during such activity. Community involvement is the process by which volunteers, amateurs, and hobbyists can contribute to collective life. A broader sort of community involvement (sometimes also carried out on a regional or societal level) comes from pursuing volunteer activities, which may be enacted as serious, casual, or project-based leisure. This, the most common conception of community involvement, is often discussed as civil labor. Civil labor, however conceived of, generates social capital. In leisure, as in most other areas of life, many activities are structured, or organized, in small groups, social networks, and grassroots organizations as well as in larger complex organizations and still more broadly, in tribes, social worlds, and social movements. The chapter ends with an examination of caring and community involvement.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.010
Scholarly communication0.0080.004
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.005

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 head0.041
GPT teacher head0.314
Teacher spread0.273 · 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
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

Citations1
Published2015
Admission routes1
Has abstractyes

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