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Record W77919102 · doi:10.4324/9780203885581-43

Issues in the management of voluntary sport organizations and volunteers

2010· book-chapter· en· W77919102 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRoutledge eBooks · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsClubCoachingVoluntary associationVariety (cybernetics)PopulationPolitical scienceTurnoverPublic relationsSport managementPsychologyManagementSociologyMedicineDemographyLaw

Abstract

fetched live from OpenAlex

In Australia, Canada, parts of Europe, and the United Kingdom, the provision of sport has a long tradition of reliance on volunteers. Volunteers perform a variety of duties ranging from coaching, maintaining grounds, and providing transportation through to senior management and development roles such as chairpersons, club secretaries, and treasurers. Volunteers come from a variety of backgrounds: some are (ex-)players who wish to pass on the experiences that they received; some are parents supporting their children’s involvement; and others are individuals helping their local community (Cuskelly et al. 2006a). Voluntary sport organizations (VSOs) vary considerably in size and complexity. The largestarea of sports volunteering activity is within sports clubs run by their members, and the majority of these operate within a governing body structure. In England there are over 100,000 sports clubs run by volunteers, involving over eight million volunteers (Taylor et al. 2003). In Australia, over 1.7 million people volunteer in sport and over a third of these contribute 140 hours or more of their time each year (ABS 2009). Research in European countries suggests that between 2.6 per cent (France) and 6 per cent of the population regularly volunteer in sport (see Coalter 2007). Volunteers are important in all facets of the sports governing body structure which may have local, regional, and national levels; even at national governing body level, volunteers play critical roles as administrators and policy makers. The relative importance of paid staff varies considerably between national governing bodies (NGBs): the few wealthy ones, such as the Rugby Football Union in England, employ considerable numbers of paid staff, both centrally and across the country, but small NGBs rely almost entirely on volunteers. In relation to this chapter, the most important feature of volunteering within sports clubs is that the clubs are relatively small and are run by volunteers themselves. Paid staff are most likely at the NGB level and, while their influence over clubs is restricted by the considerable autonomy of the clubs, they have indirect ‘control’ by directing and implementing policy. Another important area of sports volunteering is events. These vary far more in size thando sports clubs. The 2012 London Olympics will require 70,000 volunteers; the nearest comparable event in the UK, the 2002 Commonwealth Games in Manchester, required 10,500 volunteers (Ralston et al. 2004). However, there are innumerable small local events, run by clubs, local government, or a wide variety of other organizations. Unlike sports clubs, events are more likely to be managed by paid staff. Secondly, they are more likely to involve volunteerswhose commitment is restricted by time and event; what has been termed ‘episodic volunteers’ (Auld 2004). From an academic perspective, the struggle to manage volunteers and VSOs appears to stemlargely from incomplete understandings of what it means to volunteer and the process of managing sports organizations. This chapter explores three ‘management’ issues currently facing sport: first, the differences between managing VSOs and other types of organizations; second, the differences between managing volunteers and employees; and, finally, the differences in managing episodic volunteers.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.962
Threshold uncertainty score0.653

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 studies0.0000.000
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 head0.014
GPT teacher head0.274
Teacher spread0.260 · 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