COACH-PLAYER COMMUNICATIONS: AN ANALYSIS OF TOP-LEVEL COACHING DISCOURSE AT A SHORT-TERM ICE HOCKEY CAMP
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract

 Purpose: This study sought to analyze the instructional discourse of top-level coaches to identify the specific language content of coaching discourse in practice.
 Methodology: The study analyzed the recorded discourse of four coaches of the West Coast Hockey Prep Camp in Port Alberni, BC, Canada, between 2012 and 2016. Transcriptions of on-ice instructions were analyzed using Provalis QDA Miner v5.0.1 and Provalis WordStat v7.1.6 software to determine word-type and frequency. 
 Main findings: The processed corpus of 21,376 words produced 1,022 quantifiable words which were classified into one or more of the categories of single-category language (i.e. General (G), General Slang (GSl), Sports Specific (SS), and Sports General (SG)), or the eight additional multi-category sub-categories (i.e. G/GSl, G/SS, G/SG, SS/SG, GSl/SG, G/SS/SG, G/GSl/SG, and GSl/SS/SG). Analyses revealed that single-category vocabulary (i.e. G, GSl, SS, and SG) made up 75.2% of the categorized language, with SS (4.6%) and SG (11.1%) making up 15.7% of the total.
 Applications: An understanding of the linguistic framework of instructional language in short-term training camps allows athletes to invest greater focus in their athletic performance in camp. The results offer athletes contextual reference for preparatory language study and authentic linguistic insight for the counter of potential target language anxiety.
 Novelty/Originality: Results indicate that top-level coaches relied significantly less on sports-specific word-type to facilitate their instruction and suggest that a general comprehension of English can provide a strong foundation for understanding top-level coaching discourse. This provides significant insight for athletes harboring concerns for English proficiency and coach-player miscommunication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it