Negotiating digital identities: Small story narrative analysis of queer and heterosexual elite hockey playing mothers’ self-portrayals on Instagram
Bibliographic record
Abstract
OBJECTIVES: This study builds on qualitative research on elite athlete mothers and media research centring queer and heterosexual athlete mothers in elite sport. We sought to expand understanding of the less explored sexual orientation, (non)biological motherhood, and sport career, in one social media space (i.e., Instagram), in the sport of ice hockey. DESIGN: Visual/textual Instagram posts (n = 1245) of four Canadian elite hockey player mothers' -two queer non-biological mothers and two heterosexual biological mothers -were the focus of small story narrative analysis. We explored how queer and heterosexual hockey player mothers portray their identities in small stories as they negotiated motherhood and sport career. RESULTS: Two identities were identified: mumtrepeneur and generative identity. Three small stories of children on ice, children off ice, and grit and grace shaped 'mumtrepeneur' identity meanings threaded by consumerism that enhanced queer athlete mothers' visibility but revealed an economic advantage for heterosexual mothers. Two small stories of giving back to others and not without family shaped a 'generative identity' tied to growing the game for the next generation and nurturing family in careers. These findings show how hockey (non)biological mothers resist, and affirm, heteronormative mother narratives, using digital small stories. CONCLUSIONS: Small stories on Instagram enhance understanding of queer and heterosexual (non)biological mother identities and (in)visibility, in an inequitable sport system. This research shows how small stories on Instagram can be used by athlete mothers to increase visibility and marketability, while exposing additional avenues needed for equity and change concerning identity inclusion. More research using a small story approach grounded in narrative inquiry would build on understanding social media's role in shaping motherhood and sport meanings.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".