O*NET-SOC 代码
41-2022.00

Sell spare and replacement parts and equipment in repair shop or parts store.

职业名称和任务陈述按其发布时的英文原文显示。标签(包括任务类型)为译文。

AI暴露度

  • 数据来源: BLS发布时间: 2026-08

    高· 相对

    低四级相对区间很高

    职业群单位数值

    尺度 · 母数 · 来源

    四级相对类别(低 / 中等 / 高 / 很高)

    以BLS就业预测表中831个细分职业为基数。取值按 NEM(全国就业矩阵)代码给定,因此共用同一 NEM 代码的职业得到相同分档

    来源数据集(XLSX 文件下载)

  • 数据来源: Anthropic发布时间: 2026-03

    0.000

    0.000此处所载数值的范围0.745
    尺度 · 母数 · 来源

    观测暴露度指数,按发布原值0–1

    以O*NET任务映射为基准

    按 SOC 2018 职业发布的数值;具有相同 SOC 2018 代码的所有 O*NET 职业均显示此值

    来源数据集(CSV 文件下载)

  • 数据来源: ILO发布时间: 2025

    0.38

    0.09此处所载数值的范围0.70

    职业群单位数值

    尺度 · 母数 · 来源

    生成式AI暴露度指数,按发布原值0–1

    按 ISCO-08 细类(4 位)发布的数值。按原样应用美国劳工统计局(BLS)的官方对照表(ISCO-08→2010 SOC、2010 SOC→2018 SOC)关联到本职业,对应关系为全部或部分对应

    来源数据集(PDF 文件下载)

该来源发布的是什么性质的数值

BLS的类别是相对排位而非绝对水平,也不是一手测量:它把多项已发表研究给出的职业百分位排名归并为四个等级。它不是就业或工资预测,不是采用概率,也不区分自动化与增强。

AI 暴露度(OpenAI 评分标准)

已评分任务 19 项 · β ≥ 0.5 的任务 9 项(47.4%)

β = 直接暴露(E1)+ 0.5 × 借助工具时的暴露(E2),依据原始代码库的定义。

  • 原始单位:O*NET 27.2 任务 → O*NET 31.0 职业代码
  • 所有已评分任务均在 O*NET 31.0 任务列表中。
来源
OpenAI "GPTs are GPTs" exposure rubric
版本
gh-main-0471612
许可
MIT License, Copyright (c) 2024 OpenAI

任务

来自 O*NET® 31.0 Database 的任务陈述,核心任务在前。

任务类型β(OpenAI)
Read catalogs, microfiche viewers, or computer displays to determine replacement part stock numbers and prices.核心1
Determine replacement parts required, according to inspections of old parts, customer requests, or customers' descriptions of malfunctions.核心0.5
Receive and fill telephone orders for parts.核心0.5
Prepare sales slips or sales contracts.核心1
Receive payment or obtain credit authorization.核心0
Advise customers on substitution or modification of parts when identical replacements are not available.核心0.5
Examine returned parts for defects, and exchange defective parts or refund money.核心0
Mark and store parts in stockrooms, according to prearranged systems.核心0
Discuss use and features of various parts, based on knowledge of machines or equipment.核心1
Demonstrate equipment to customers, and explain functioning of equipment.核心0
Place new merchandise on display.核心0
Measure parts, using precision measuring instruments, to determine whether similar parts may be machined to required sizes.核心0
Repair parts or equipment.核心0
Fill customer orders from stock, and place orders when requested items are out of stock.核心0.5
Assist customers, such as responding to customer complaints and updating them about back-ordered parts.核心0.5
Locate and label parts, and maintain inventory of stock.核心0
Pick up and deliver parts.核心0
Maintain and clean work and inventory areas.核心0
Manage shipments by researching shipping methods or costs and tracking packages.核心0.5

职业信息

来源与署名

This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.

Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.

O*NET OnLine: 41-2022.00 Parts Salespersons

KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.

完整署名与许可