particle_expertise_resolve

Turn free text into the occupation and field-of-research codes that the speaker-expertise filters take. Free.

Turn free text into the codes that every speaker-expertise filter takes: SOC 2018 occupations (with their ISCO-08 equivalents) and ANZSRC 2020 fields of research. "cardiologist" finds SOC 29-1212 Cardiologists; "finance" finds the finance fields. Words match in either number and by prefix, so "cardio" and "cardiologists" work too.

Call it first whenever a question restricts who is speaking by occupation, profession, credentials or industry (“doctors”, “medical professionals”, “economists”, “people in finance”, “lawyers”): the expertise filters, not search wording, decide who speaks. Call it again when a filter returns unresolved_reference, then retry with a code it returns. Never drop the filter.

Each code comes back with its slug, level, parent and the parameters that accept it:

• occupation / field on particle_podcast_list_guests and particle_expertise_get.
• guest_occupation / guest_field on particle_podcast_find_mentions, particle_podcast_list_episodes, particle_podcast_search_transcripts, particle_podcast_get_episode_timeseries and particle_podcast_resolve.

Every one of those parameters accepts the code, the slug or the title, in either number (cardiologist or cardiologists). A broad code (a SOC major, minor or broad group, an ANZSRC division) filters everything below it, and so does an everyday name such as doctors or medical-professionals. A word no occupation answers well lands on the one field of research or capacity it names: "oncologists" finds field 3211 Oncology and carcinogenesis and "investors" field 350208, and either works as guest_occupation too. "founders", "politicians", "pundits" and "influencers" name capacities, which no code holds. Pass parent to walk the hierarchy one level down: below a SOC major group its minor groups, then broad groups, then detailed occupations; below a division its groups. Omit both query and parent to list the top level.

This tool is free. Resolve a code here before you pass one to a filter: an occupation or field that names nothing returns unresolved_reference with the closest codes.

It does not resolve people or companies. Use particle_person_resolve, particle_company_resolve or particle_entity_resolve for those. It is not the topic taxonomy either: particle_topic_browse classifies what episodes are about, and these codes classify what speakers know.

Inputs

Field	Type	Required	Default	Description
query	string	no	—	Free text naming an occupation or a field of research (e.g. "cardiologist", "financial analyst", "constitutional law"). Singular or plural; words match by prefix. Omit with parent to list that code’s children, or omit both to list the top level.
standard	string	no	any	Which codes to search: occupation (SOC 2018, with ISCO-08 equivalents), field (ANZSRC 2020 fields of research), or any for both. With any, occupations and fields are interleaved so neither crowds out the other.
parent	string	no	—	A code, slug or title whose children to list (e.g. "29-0000" for the healthcare occupations, or "38" for economics). With query, searches only below it.
limit	integer (1–25)	no	5	Maximum codes to return.

Output

A markdown document headed ## Expertise codes matching "<query>" (N) (or under <parent>, or — top level when neither is set), then one H3 section per code, titled with the code’s official title:

• **Standard:** — soc_2018, isco_08, or anzsrc_for_2020.
• **Code:** and **Slug:** — the two handles a filter takes (the title works too).
• **Level:** — depth in the standard: SOC major group 1, detailed occupation 2; ANZSRC division 1, group 2, field 3.
• **Parent:** — Title (code, slug), omitted at the top level.
• **Children:** — how many codes sit one level down, with the parent value that lists them.
• **ISCO-08 equivalents:** (or **SOC 2018 equivalents:** for an ISCO code) — the crosswalk counterparts, each as Title (code, slug).
• **Use as:** — the exact parameter assignments that accept the code, and the tools that take them.

When the query names a capacity, a paragraph saying so and a ### Capacity: <name> section come first, with **Means:** (what the capacity covers) and **Use as:** (capacity on particle_podcast_list_guests, guest_capacity on the episode and mention tools). particle_expertise_get describes codes only, so it does not take a capacity.

## Expertise codes matching "founders" (0)

"founders" names a capacity rather than an occupation: filter by it with the capacity parameters.

### Capacity: executive_founder

**Means:** runs or founded a company or organization
**Use as:** capacity="executive_founder" (particle_podcast_list_guests) · guest_capacity="executive_founder" (find_mentions, list_episodes, search_transcripts, get_episode_timeseries)

When nothing matches, a single paragraph suggests one distinctive word or its start, the other standard, or browsing from the top.

Sample (query="cardiologist"). Words match by prefix, so a field shows up for a query that starts its words: "cardiolog" also finds Cardiology (incl. cardiovascular diseases).

## Expertise codes matching "cardiologist" (1)

### Cardiologists

**Standard:** soc_2018
**Code:** 29-1212
**Slug:** cardiologists
**Level:** 2
**Parent:** Healthcare Practitioners and Technical Occupations (29-0000, healthcare-practitioners-and-technical-occupations)
**ISCO-08 equivalents:** Generalist medical practitioners (2211, generalist-medical-practitioners); Specialist medical practitioners (2212, specialist-medical-practitioners)
**Use as:** occupation="cardiologists" (particle_podcast_list_guests, particle_expertise_get) · guest_occupation="cardiologists" (find_mentions, list_episodes, search_transcripts, get_episode_timeseries, podcast_resolve)

Example

Agent calls: particle_expertise_resolve {
  "query": "financial analyst",
  "standard": "occupation"
}

Walking the hierarchy, from a division to its groups:

Agent calls: particle_expertise_resolve {
  "parent": "38",
  "limit": 25
}

Related

• REST equivalents: GET /v1/people/occupations and GET /v1/people/fields, with q to search and parent to walk the hierarchy.
• See who an occupation or field books, and where, with particle_expertise_get.
• Read the codes a person is listed under with particle_person_get and include: ["expertise"].