A Worldwide Review of Selection for Air Traffic Control Personnel
Bibliographic record
Abstract
Air traffic control is a highly technical occupation that requires emotional stability, considerable aptitude, and lengthy training. Identifying those individuals with the greatest potential to capitalize on training is a major interest of air traffic organizations around the world, particularly when considering limited resources. This paper compares and contrasts several selection systems, to include their development, continuing validation, and in one case, demise. In the erstwhile, two-stage US Federal Aviation Administration (FAA) selection process, applicants completed the written Office of Personnel Management (OPM) test battery and a nine-week screening program at the FAA Academy in Oklahoma City, OK. The eventual replacement to this system, the Air Traffic Selection and Training (AT-SAT) computerized test battery, is now used to assess aptitude for air traffic control duties. The US Navy and Air Force’s use of composites from the Armed Services Vocational Aptitude Battery (ASVAB) is next explored. The computerized battery employed by EUROCONTROL, termed the First European Air traffic Selection Test (FEAST), is then considered. FEAST is used by many European countries to complement their existing selection methods. To the delight of researchers worldwide, users are required to agree to assist in the continuing validation of FEAST. Finally, the approach used by SHL Canada to recruit and select trainees for NAV CANADA Air Traffic Control positions using a variety of cognitive ability and personality measures is described, including the associations found between cognitive measures, ability tests, and performance in both initial and on-the-job training.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".