Tangled and Bumpy Roads to Gender Equity: Socio-Cultural Insights from Media Stories About Olympic Athletes and Motherhood
Bibliographic record
Abstract
With the 2024 Olympic Games touted as reaching gender parity (i.e., same number of female and male athletes participating), media conversations are continuing about elite athlete mothers. Researchers interrogating media stories of Olympic athlete mothers have shown that their sporting journeys are not straightforward due to tensions linked to gender (in)equity. In this paper we use narrative inquiry as a theoretical lens to explore “comeback themes” synthesized from published media studies of Olympic athlete mothers, along with recent examples of media stories of Olympic athlete mothers. We discuss four comeback themes that include: (in)compatible identities, super mums, veteran status/age, and exposing discrimination, and some implications for gender equity. The first three comebacks perpetuate gender ideologies of heteronormative femininity, good motherhood, ageism, and exceptionalism, which downplay equitable support and change. These themes, along with the exposing discrimination theme, also highlight shifting media representations of motherhood and sport whereby stories expose struggles, realities, and/or structural deficits. We reflect on these themes as a “tangled and bumpy road” to gender equity led by athlete mothers’ voices resulting in changes in maternity rights. These comeback themes show gains in gender equity for sportswomen and highlight areas where more work is needed. Future research recommendations include studying mainstream and social media spaces with an intersectional lens to expand understanding of media stories as pedagogical resources to learn more about motherhood, sport, and gender (in)equity.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".