Balancing Control and Affiliation in Coaching: An Interpersonal Circumplex Analysis of Athlete Outcomes
Bibliographic record
Abstract
For coaches, a tension exists between traditional authoritarian (i.e., controlling, strict) and modern supportive (i.e., affiliative, caring) interpersonal styles. Coaches are expected to balance control (i.e., dominance) and affiliation (i.e., relational care), to win and facilitate athletes’ well-being. Although there’s evidence that authoritarian coaching styles undermine athletes’ performance and engagement (Carleton et al., 2016; Zogg et al., 2024), there’s also evidence that control is necessary (Brinton et al., 2017; Taylor et al., 2022) and that overly affiliative coaching styles may hinder motivation and commitment (Jin et al., 2022). Balancing authority and support appears central to coaching, yet researchers have often treated control and affiliation as separate or opposing constructs rather than interrelated dimensions that jointly shape coaches’ interpersonal styles. While existing research provides evidence that coaches’ balancing control and affiliation is beneficial, how coaches should balance these dimensions to promote different desired athlete outcomes remains unclear. The present study extends existing research by applying the interpersonal circumplex to plot coaches’ interpersonal styles (i.e., coaching styles) along two orthogonal (i.e., unrelated) dimensions — control and affiliation. The purpose of this research project is to map athletes’ outcomes within the circumplex space to provide a more sophisticated understanding of the relative degree of coach control and coach affiliation that are most associated with different athlete outcomes. Student-athletes at Canadian and U.S. institutions who are actively participating in university or college athletic programs will complete an online survey that includes measures of their identified coaches' perceived interpersonal styles and interpersonal problems, as well as measures related to three athlete outcomes: coach-athlete relationship quality, athlete performance, and athlete burnout. In brief, we expect that desired athlete outcomes will correspond with coaching styles that exhibit moderate control and moderate affiliation, while undesired athlete outcomes will correspond with coaching styles that exhibit elevated control and lowered affiliation. Our hope is that these findings will be used to inform interventions that help coaches evaluate and adjust their interpersonal styles to foster stronger coach-athlete relationships, enhance performance, and prevent athlete burnout.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.008 | 0.020 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".