Tamminen et al (2017) Car Ride Home
Bibliographic record
Abstract
Purpose: Conversations occurring within the car ride home may shed light on parental socialization among adolescent athletes, as conversations are viewed as sites to socialize participants as members of the group or family. Parent-athlete communication also occurs within a broader social context of youth sport, where narratives regarding performance and parenting may shape the ways in which parents and athletes communicate and make sense of their experiences. The purpose of this study was to explore conversations between adolescent athletes and parents during the car ride home following sport practices and competitions.Methods: Twenty-seven athletes and one of their parents participated in individual semi-structured interviews. Thematic, structural, and performative narrative analyses (Reissman, 2008) were used to examine parent and athlete accounts of conversations during the car ride home. Results: Results pertained to participants’ experiences of enjoying versus enduring the car ride home, privacy, and narratives of performance in youth sport. Participants’ stories about the car ride home normalized parental feedback as useful and necessary for performance improvement, and conversations were often reported to differ depending on who was present in the car. We identified strategies that athletes used to navigate difficult conversations, and participants provided suggestions about strategies to improve the conversation during the car ride home. The findings are discussed in relation to narratives of performance and good parenting in youth sport, and in terms of parent behaviours in public versus private settings.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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".