Military correspondence methods

From military descriptions to civilian occupations

TaskMatch retrieves O*NET task IDs from military duty descriptions. Task similarity connects those descriptions to posting-derived civilian occupation-task profiles. Established military-to-civilian crosswalks provide a comparison: among 1,091 military titles with an eligible crosswalk occupation, 647 (59.3%) have a crosswalk match in the task model’s top twenty recommendations. Crosswalk agreement is not evidence that a transition is feasible or that a worker meets licensing, education or experience requirements.

How AI is used

Retrieval: TitleMatch and TaskMatch use embedding similarity to match input text to existing occupation codes and O*NET task IDs. Retrieved task statements come from the taxonomy.
Generative-model review: selected posting task–occupation assignments and the OSHA task bundle use model judgments. Their review procedures and decisions are documented with each analysis; those judgments are not independent expert validation.
Website and audit: Codex helped create the layout, code and explanatory text, and performed the disclosed computational audits. Tables and charts report calculations from the linked inputs. Audit checks do not replace researcher review.

Use the linked code, source versions and review records to inspect each step. Some construction inputs require authorized access.

Website layout and explanatory text were prepared with generative AI (Codex). Data sources, model methods and code.

The National Labor Exchange (NLx) Data Trust bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the authors and not of the NLx Data Trust members or others.