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Enregistrement W6939947067 · doi:10.6084/m9.figshare.28382267.v1

Cultivating legacies and connections: A narrative analysis of Instagram stories of retired elite athlete mothers through an ethic of care lens

2025· other· en· W6939947067 sur OpenAlexaboutno aff

Notice bibliographique

RevueFigshare · 2025
Typeother
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueMycorrhizal Fungi and Plant Interactions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésNarrativeEliteNarrative inquirySituatedContext (archaeology)MainstreamQualitative researchIdentity (music)MasculinityDiscourse analysis

Résumé

récupéré en direct d'OpenAlex

Although significant research has focused on athlete mothers returning to competition, the experiences of retired athlete mothers remain largely unexplored. In this study we explored the less studied research path of motherhood and sport retirement to learn more about these athletes’ lives. We sought to build on sport media research centralizing elite athlete mothers and qualitative research on athlete mother career transitions, to provide insight into identities post-elite sport in a cultural context (i.e., Instagram). The precise aim was to explore how identities intertwined with ethic of care meanings in digital stories and the psycho-social implications during retirement. Two retired Canadian athlete mothers’ (i.e., mountain biker Catharine Pendrel and boxer Mandy Bujold) Instagram posts (n = 72 for Pendrel, n = 162 for Bujold) were subjected to big and small story narrative analysis. A big story of legacy through generativity was identified and linked with ethic of care meanings depending on three small stories: giving back, inspiring the next generation, and self-connections through sport. These findings show how a concern for current and future generations through pro-social behaviors (e.g., philanthropy, imparting wisdom, time with children) are intertwined with multiple relational identities (e.g., elite athlete, mother, mentor, generative athlete) and nuanced ethics of care (e.g., self-care, everyday acts of situated caring). We conclude with what these findings and digital stories offer practitioners, closing with future research suggestions. We used a big and small story approach to explore Instagram posts of athlete mothers to understand identities and ethic of care meanings in retirement. Findings show the value of digital stories to learn more about relational identities grounded in a continuum of caring and pro-social behaviors, and how these assist with sport retirement adjustment. A big and small story approach extends understanding of elite athlete mothers’ career transitions and can stimulate conversations about the content of personal and public stories in digital spaces as resources.To stimulate such conversations, practitioners might explore elite athlete mothers’ posts on social media spaces (i.e., Instagram) by asking questions about retirement adjustment in relation to a ‘generative athlete’ identity. Questions might include, “how is family portrayed and talked about post-sport career?,” “is the athlete showing aspects of their private lives—good or bad—for others to learn from? What lessons are gained from these?”Small stories of giving back, inspiring the next generation, and self-connections through sport that shape a legacy through generativity big story, can also be used as resources to show athlete’s the benefits of relational identities and practices that assist with athlete mothers’ adaptation in retirement. A big and small story approach extends understanding of elite athlete mothers’ career transitions and can stimulate conversations about the content of personal and public stories in digital spaces as resources. To stimulate such conversations, practitioners might explore elite athlete mothers’ posts on social media spaces (i.e., Instagram) by asking questions about retirement adjustment in relation to a ‘generative athlete’ identity. Questions might include, “how is family portrayed and talked about post-sport career?,” “is the athlete showing aspects of their private lives—good or bad—for others to learn from? What lessons are gained from these?” Small stories of giving back, inspiring the next generation, and self-connections through sport that shape a legacy through generativity big story, can also be used as resources to show athlete’s the benefits of relational identities and practices that assist with athlete mothers’ adaptation in retirement.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,026
Score d'incertitude au seuil0,051

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,010
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0070,006
Communication savante0,0050,005
Science ouverte0,0010,004
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,038
Tête enseignante GPT0,281
Écart entre enseignants0,243 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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