Personal Construct Theory and Parents’ Perceptions of Developing Girls Through Sport
Bibliographic record
Abstract
Despite increased participation across all sporting contexts, many sports are still thought to be more or less appropriate for female athletes to engage with based on biologically or socially constructed characteristics (Plaza et al., 2017; Abadi & Gill, 2020). Further, the persistence of gender stereotypes continues to impact the participation levels of girls in sport; particularly in traditionally masculine sports (Tucker Center, 2018; Staurowsky, 2016). Given the influence parents can have in dictating their children’s participation in sport (Dorsch et al., 2020), the objective of the present study was to explore how parents perceive their daughters’ participation in traditionally boy-dominated sport. Semi-structured interviews were conducted with eight parents of daughters currently engaged in traditionally boy-dominated sports at a competitive level. A laddering interview technique—based on the personal construct theory—was used as a basis for the interview guide (Bourne & Jenkins, 2005). This technique allowed the interviewer to elicit participants’ higher-level constructs, revealing their overarching values more effectively. Three themes were constructed through the assessment of the interviews, these being that parents believe participation in non-traditional girls’ sport provides young female athletes with (a) the capability to identify gender inequality more easily, (b) opportunities to face unique challenges and shed the perceived limitations imposed upon girls, and (c) opportunities to express less stereotypically feminine traits and, therefore, to grow. These results suggest that parents of daughters who participate in traditionally boy-dominated sports perceive these sports to contribute to building several positive aspects of their daughters’ development.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".