An inventory of the South african fitness industry
Bibliographic record
Abstract
Objective. The aim of this study was to create an inventory of fitness facilities in South Africa, their location, equipment and services offered, and the demographics, education and training of the staff working in these facilities. Design. A total of 750 facilities were identified, and descriptive data were gathered from 442 facilities (59%) with the use of a questionnaire administered telephonically and via the website of the Sports Science Institute of South Africa. Setting. The study was initiated by the Sports Science Institute, and the results were presented at the 4th Annual Discovery Vitality Fitness Convention on 4 May 2006. Results. Results show that the industry comprises mainly independent facilities (68%). All types of facilities were found to be located mostly within urban areas, and reported providing services to just less than 2% of the South African population. Facilities offer a wide range of equipment and services to their members. Of the fitness-related staff at facilities, the majority were reported to be young (18 - 25 years, 55% of male, and 49% of female staff), and in terms of racial proportions most staff were white (males 40% of total staff and females 33% of total staff).Less than a quarter of fitness-related staff hold university qualifications, and just over 80% of instructors hold qualifications aligned with the National Qualifications Framework. The importance of education and training of staff was emphasised by respondents. Conclusions. This report highlights the widespread value of assessing the fitness industry, particularly within the context of the rise of chronic diseases in South Africa and government initiatives to promote healthy lifestyles. South African Journal of Sports Medicine Vol. 18 (3) 2006: pp. 93-104
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".