Application readiness research method

Q: What should the research method define before analysis?

Define the question, population, sample, observation period, inclusion rules, exclusions, and outcome before inspecting patterns.

Q: How should personal data be protected?

Use only data needed for the question, limit access and retention, and aggregate or suppress groups that could identify a person.

Q: Can an observed pattern become a hiring rule?

No. Report uncertainty and plausible alternatives, and keep observation separate from recommendation or prediction.

Q: When should the method be reviewed again?

Review it when the source, sample, definition, product behavior, or observation window changes, and keep the review date visible.

See the proposed inputs, sampling rules, exclusions, privacy safeguards, and reporting limits for application readiness research method. No aggregate claim is published until the required evidence and review threshold is met.

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Methodology explains a preparation signal; it does not turn the result into a hiring prediction.

Application readiness is a set of checks, not a hiring probability

Compare one versioned resume and its evidence with one dated job posting. Report supported, missing, conflicting, or unverified items without turning them into a chance of being hired.

What material does this specific application still need before submission?

Verified public facts

31.0Database release2026-08-27

O*NET 31.0 organizes worker and job information across skills, knowledge, abilities, tasks, work activities, work context, occupations, and related domains.

How to use it: A defensible vocabulary for role requirements and work evidence categories.
What this data cannot establish: That every task or skill applies to a particular opening or candidate.

2026-08-27

Korea’s NCS public data describes work through the competency units required to perform it, providing a Korean reference alongside occupation data built for the U.S. labour market.

How to use it: Korean role and competency framing without translating U.S. occupation labels literally.
What this data cannot establish: A vacancy count, hiring trend, salary, or employer-specific requirement.

How the data is handled

Freeze the inputs
Store the exact job URL, posting observation date, resume version, and evidence identifiers before analysis.
Classify, then explain
Label each material requirement as supported, partial, missing, conflicting, or unverifiable and link the evidence behind the label.

Definitions that travel with the result

Supported requirement: A job requirement connected to a specific resume passage and its source work evidence.
Unverified claim: A claim in the application that has no linked source record or conflicts with the source.

Results that still require observed data

Application gap register

Which material requirements are supported, missing, conflicting, or still unverified?

Awaiting observed data

Required result fields

Target job identifier
The exact job posting used for the comparison.
string · required
Resume identifier
The versioned resume used in the analysis.
string · required
Evidence identifier
The source work record supporting a resume or application claim.
string · required
Observed at
The date Refresh retrieved or checked the record.
date · required
Category
A documented category with a stable definition.
string · required
Metric definition
The exact inclusion, exclusion, and calculation rule.
string · required

Publish only when: Publish the result only for immutable input versions with a linked explanation for every material label.
Awaiting observed data: Add a real job, a versioned resume, and source evidence to produce this result.

What this data cannot establish

The analysis cannot know an employer’s hidden rubric, applicant pool, or final decision process.
Occupation standards help organise requirements; the actual posting remains the primary target.

How to use it

Resolve conflicting or unsupported claims before polishing the wording.

Official data sources

O*NET DatabaseU.S. Department of Labor, Employment and Training Administration2026-08-27
Coverage
Worker and job characteristics, including occupations, tasks, work activities, skills, knowledge, and work context.
Boundary
O*NET describes occupations in the U.S. economy. It does not reproduce one employer’s job description or prove that a candidate has a skill.
Korea National Competency Standards dataHuman Resources Development Service of Korea2026-08-27
Coverage
Korean competency standards and competency-unit information used to describe work by the capabilities required to perform it.
Boundary
NCS is a competency standard, not a live count of vacancies, resumes, interviews, or hiring outcomes.

Career evidence research methods

Review proposed samples, exclusions, privacy safeguards, and reporting thresholds before refresh.cv publishes aggregate career findings.

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Job-search market research method

See the proposed inputs, sampling rules, exclusions, privacy safeguards, and reporting limits for job-search market research method. No aggregate claim is published until the required evidence and review threshold is met.

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Frequently asked questions

What should the research method define before analysis?

How should personal data be protected?

Can an observed pattern become a hiring rule?

When should the method be reviewed again?

Read the result with its method and limits.

Use the relevant methodology before deciding which finding to act on.

Open the relevant workspace