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Record W7009596840

Exploring How The Covid-19 Pandemic Affected Coaches’ Relationships With Athletes On Adolescent Travel Sport Teams

2022· other· en· W7009596840 on OpenAlexaboutno aff

Bibliographic record

VenueHuman Biology · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicAthletesPerspective (graphical)PerceptionYouth sportsHuman factors and ergonomicsBurnoutQuality (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study is to explore how the COVID-19 pandemic has affected coach-athlete relationships for coaches of Ontario, Canada-based adolescent travel sports teams. From March of 2020 until May 2021 multiple Ontario youth travel sports organizations canceled/postponed their 2020-2021 seasons because of the worldwide COVID-19 pandemic. Therefore, it is expected that the stoppage of travel adolescent sports in Ontario affected coaches' ability to develop quality coach-athlete relationships. Developing high-quality coach-athlete relationships for coaches and athletes have been positively associated with satisfaction, happiness, and lower levels of burnout within sports. Therefore, qualitatively understanding if and how the COVID-19 pandemic affected coach-athlete relationship development from coaches’ perceptions is valuable information for youth sports organizations so that they can provide positive sporting experiences for coaches and athletes. Six to 15 adolescent travel sport coaches will be recruited from provincial sport organizations (e.g., Dive Ontario) in Ontario. Coaches will be asked to complete a 60–90-minute semi-structured interview via Zoom technology to: explore how the COVID-19 pandemic has impacted their ability to develop their coach-athlete relationships, what strategies they used to cultivate relationships with their athletes during the COVID-19 pandemic and what were the differences and similarities of developing coach-athlete relationships before and during the COVID-19 pandemic from the perspective of the coaches.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.326
GPT teacher head0.318
Teacher spread0.009 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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