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Volunteer Work, Inclusivity, and Social Equality

2018· book-chapter· en· W2916232379 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

VenueOxford University Press eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsQueen's University
Fundersnot available
KeywordsWork (physics)Labour lawSpace (punctuation)Public relationsEmployment discriminationSociologyPolitical scienceLawEngineering

Abstract

fetched live from OpenAlex

This chapter argues that current attempts in employment law to distinguish volunteers from employees on the basis of volunteer work’s civic, humanitarian, or charitable character are premised on overly narrow views of the moral significance of work. The chapter proposes that the law distinguish volunteer work from employment on the basis of the work’s <italic>merit inclusivity</italic>—inclusivity with respect to skill and ability. By offering people access to a broader range of social projects than their skills might offer in the labour market, merit inclusive volunteering opportunities can lessen the risk that skill and ability will confine people to particular social roles. Distinguishing volunteers from employees on the basis of merit inclusivity can thus create a more principled volunteer–employee legal boundary and can preserve legal space for work that lessens inegalitarian effects of the labour market on opportunities to participate in social life.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.988
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

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

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 head0.035
GPT teacher head0.239
Teacher spread0.204 · 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