An Analysis of the Effect the Enlisted Grade Structure Review Has Upon First Term Alignment Plan Retention Requirements
Bibliographic record
Abstract
This analysis was conducted to determine whether the Enlisted Grade Structure Review (EGSR) has a significant effect on First-Term Alignment Plan (FTAP) retention requirements. It provides a background of first-term retention in the all-volunteer force by examining, not only the retention behavior of the United States military, but also the retention of Canadian and Australian military forces. Furthermore, it investigates elements of the Enlisted Career Force Controls Program. It provides an explanation of the pre- and post-EGSR skill grade flow rates and pay grade structure data used in the research. The current Marine Corps enlisted grade structure is compared to the proposed enlisted grade structure from the August 27, 2002 Officer and Enlisted Grade Structure Review to determine whether the EGSR affected FTAP retention requirements. The research found that the EGSR had a positive effect on FTAP. The EGSR changed many military occupational specialties to a logical pyramidal shape facilitating promotion opportunities. Marines will more likely remain on active duty when promotion opportunities are visible. Restructuring the enlisted billets into a pyramidal shape will support the Marine Corps' operating forces. Marine Corps operational readiness is increased when the number of Marines in the lower pay grades are available in sufficient numbers to support the next immediate pay grade. The research shows that a pyramidal shaped MOS structure naturally retains the required numbers to support the Marine Corps. Only retention-critical MOSs must still be supported by an SRB to ensure Marines are not drawn away from the Marine Corps by more lucrative offers in the civilian sector.
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 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 | 0.038 | 0.234 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".