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Record W7027249201

CFL Chaplaincy: How do CFL Chaplains Act in Consultation Towards Ethical Decision Making?

2023· article· en· W7027249201 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsEthical codeFootballAthletesLeagueCode of conductEthical standardsEthical issuesChristian ministry
DOInot available

Abstract

fetched live from OpenAlex

Abstract\nAlthough the literature on sport ethics and religion has expanded in recent years, there is little research on the role and concept of “sports chaplaincy” within Canada (Parry, 2007) (Watson, Parker & White, 2016) (Watson, Parker & Adogame, 2018). The Canadian Football League (CFL) chaplaincy program offers a unique form of ministry that has the potential to influence athlete’s ethical behavior. The chaplain's ‘holistic’ counselling approach is not only concerned with the CFL professional’s on-field job performance but offers emotional and spiritual support for every facet of a CFL professional’s life (Roe, 2016; Cheney, 2019). In the sport ethics literature, there is, and continues to be, a vastness of incidences whereby sporting professionals breach ethical policies. These incidences include, but are not limited to; impaired driving, domestic abuse, hazing, excessive violence, the use of performance enhancing substances etc. (Mihoces, 2014) (Mitchley, 2014) (Schmidt, 2014) (Fogel, 2013). These breaches in ethical policy, and codes of conduct transgressions reflect poorly on the athletes, their professional franchises and society abroad (Dungy, 2009) (Maston, 1967). From a sport chaplaincy perspective, and referencing the current sport ethics literature, my thesis question asked how CFL chaplaincy programs influence the ethical behavior of CFL professionals? Amid analyzing this phenomenon, one aspect of my research investigated the indirect benefits and concerns for athletes who follow the ethical guidelines that the CFL chaplains promote.\nProfessional sports culture is an extremely competitive vocation and one where job security for players and coaches is determined by immediate and sustainable success (Gamble, 2013, pp. 250-251). Within this competitive culture, athletes and coaches often fall into customs wayward from Christian ethics, sport ethics, and common ethics (Fogel, 2013). In addition, recent sport chaplaincy literature has indicated that western society is more ‘humanistic’ than Christian, and our current ‘post traditional religious society’ resembles more of a ‘spiritual marketplace’ than formal religiosity (Uszynski, 2016) (Kumar, 2013) (Nesti, 2010) (Cheney, 2019). One question is: does the shift in spirituality have a positive or negative effect on athlete’s physical health, mental health, and ethical conduct within the realm of professional sports? In addition, how do CFL chaplains promote their worldview amid an increasingly secular and multicultural society? This thesis aims to provide some answers and insights to aspects of these crucial questions.\nAdditionally, there is evidence within the sport-ethics literature suggesting high level athletes are more likely to experience divorce, mental illness, depressive disorders, and spousal abuse than the general population (Stephenson, 2014) Reardon & Factor, 2010) (Mummery, 2005). Some of these psychiatric disorders, and breaches in ethical conduct, have been associated with the ‘win at all costs’ mentality: over-training, unbalanced schedules, substance abuse, eating disorders and times of transition (i.e., post-injury or retirement) (Reardon & Factor, 2010) (Mummery, 2005) (Baum, 2000, 2003) (Watson, 2007). This thesis has investigated the CFL chaplain’s role in providing ethical counsel to CFL professionals amid the threat of these issues. Moreover, this thesis analysis how CFL chaplains provide ethical counsel within the distinctive culture of the Canadian Football League.

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.118
GPT teacher head0.392
Teacher spread0.275 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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