Exploring the role of socioeconomic status and psychological characteristics on talent development in an English soccer academy
Bibliographic record
Abstract
Social factors and psychological characteristics can influence participation and development in talent pathways. However, the interaction between these two factors is relatively unknown. The aim of this study was to investigate the implications of socioeconomic status and psychological characteristics in English academy soccer players (n=58; aged 11 to 16 years). To assess socioeconomic status, participants’ home postcodes were coded according to each individual’s social classification and credit rating, applying the UK General Registrar Classification system and CameoTM geodemographic database, respectively. Participants also completed the six factor Psychological Characteristics for Developing Excellence Questionnaire (PCDEQ). A classification of ‘higher-potentials’ (n=19) and ‘lower-potentials’ (n=19) were applied through coach potential rankings. Data were standardised using z-scores to eliminate age bias and data were analysed using independent sample t-tests. Results showed that higher-potentials derived from families with significantly lower social classifications (p=0.014) and reported higher levels for PCDEQ Factor 3 (coping with performance and developmental pressures) (p=0.007) compared to lower-potentials. This study can be used to support the impetus for researchers and practitioners to consider the role of social factors and psychological characteristics when developing sporting talent. For example, facilitating player-centred development within an academy and, where necessary, providing individuals with additional support.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".