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Record W2086377945 · doi:10.1108/sbm-01-2012-0001

Assets and obstacles: an analysis of OUA hockey from the coaches’ perspective

2013· article· en· W2086377945 on OpenAlex
Chris Chard, Craig Hyatt, William Foster

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSport Business and Management An International Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Strategy and Culture
Canadian institutionsUniversity of AlbertaBrock University
Fundersnot available
KeywordsLeagueIce hockeyMarketingPsychologyContext (archaeology)Public relationsProfessional sportFootballBusinessPolitical science

Abstract

fetched live from OpenAlex

Purpose The passion of Canadians for ice hockey is well documented; however, university teams in Canada are routinely ignored by consumers and the media. The authors’ goal was to better understand the context in which Ontario university hockey struggles and to address the theoretical question of how best to examine and evaluate the problems of sport‐specific organizations. Using the Value Dynamics Framework (VDF), the purpose of this paper was to examine whether or not this framework fits well with the realities facing not‐for‐profit OUA hockey teams, and if not, to create a framework specific to these teams. Design/methodology/approach Semi‐structured in‐depth interviews were conducted with 15 of the 19 (77 percent) OUA hockey coaches during the 2010/2011 hockey season. The interview guide was drawn from the VDF elements and enabled the researchers to understand not‐for‐profit organizational assets, including physical, financial, employee/supplier, customer, and organizational. Findings This paper offers empirical insights about the assets and obstacles facing the OUA hockey league and its teams. For example, players, coaches, affiliation with universities, and the hockey product are noted assets. Obstacles for strategic growth include arenas, suppliers, media attention, financial sustainability, parity with other leagues in Canada, and leadership. The VDF proved a useful foil to suggest that something is needed that more accurately represents sport management‐specific situations. Research limitations/implications The main limitation of this study is that it lacks generalizability. Although motivated to better understand not‐for‐profit sport in general, the authors’ model is specific to OUA men's hockey teams. However, their OUA hockey team‐specific revised VDF does provide insights into the assets available to coaches, and also acknowledges the corresponding challenges or obstacles surrounding the asset classes in the context of OUA hockey. Practical implications This paper provides an approach towards making a more generalizable not‐for‐profit sport model that could help explain the success (or lack of success) of such organizations. Originality/value This study addresses a need to develop a framework to examine and evaluate not‐for‐profit sport‐specific organizations, such as the teams in the OUA.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.854

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 communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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