“Our Ginny”: Virginia Wade, the 1977 Wimbledon Championships and the Gendering of National Identity
Bibliographic record
Abstract
Within sport media, it is customary for sportsmen rather than sportswomen to be accorded the privileges and responsibilities of competing not just for the nation but also on behalf of it. However, under certain circumstances, it is apparent that the typically gendered media conventions may shift to accommodate nationally important sportswomen. This study concerns the British tennis player Virginia Wade, and via a textual analysis, the print-media discourse surrounding her 1977 Wimbledon triumph is analyzed. It is argued that the wider sociohistorical and personal contexts of her victory helped facilitate a shift, whereby her national identity rather than her gender becoming the primary media frame. Not only was Wade’s win considered significant amidst the mid-1970s economic downturn in Britain, it also coincided with Wimbledon’s centenary and a visit by the Queen during jubilee year. Consequently, her victory was imbued with national symbolism through displays of “banal nationalism.” Coupled with Wimbledon’s “invented traditions,” Wade was represented as embodying the British “imagined community” through her play and approach. This study’s findings reassert the importance of examining the intersections of gender and national identity in sport media and urges for more research that foregrounds historical context as a key factor for female athlete national transcendence.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".