Understanding athlete mother transition in cultural context: A media analysis of Kim Clijsters’ tennis comeback and self-identity implications.
Bibliographic record
Abstract
Although the presence of elite athlete mothers is growing in sport, these athletes have received less attention in sport psychology research. The purpose with this study was to extend understanding of elite athlete mothers in sociocultural context by examining how news media constructed elite athlete identities of 1 high profile athlete mother, tennis star Kim Clijsters. Ethnographic content analysis (Altheide, 1996) was used to explore motherhood and athletic identity in relation to an athletic comeback, as sociocultural creations shaped by media narratives, with psychological implications. Forty-five stories from North American and United Kingdom news media were collected between August 1, 2009, and September 30, 2009, covering the key media incident of Clijsters comeback to win the 2009 U.S. Open. Visual data analysis of 38 images further contextualized the meaning(s) of narratives identified within stories (Altheide & Schneider, 2013). A fairy tale come true narrative was identified as constructing comeback meanings linked to 2 identities: the super mum and the golden girl. These identities fed into a limited meaning of Clijsters tennis comeback, downplaying accomplishments in favor of normative ideals for female athletes, but also expanding possibilities for athlete mothers. These findings extend cultural sport psychology research exploring the social construction of elite mother athlete identities and athlete transition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".