A frequent need in organizations and organizational research is to classify individual positions or jobs into groups, with each group internally homogeneous in terms of a profile of relevant psychological characteristics (e.g., abilities) and situational characteristics (e.g., job requirements) and at the same time externally distinct from all other groups. A job typology is either an established framework—and several major ones will be reviewed here—or it is derived through analytic procedures applied to data at the individual and/or job level, but in either case job typologies contain groups of jobs that, to a greater or lesser extent, adhere to the aforementioned principle of internal consistency and external distinctiveness. This classification process is similar in spirit to factor analysis, in the sense that it results in a small yet sensible number of groups to simplify and amplify relevant similarities and differences. Rather than serving as an end in itself, however, job classification is a tool that can assist in a whole host of personnel-related functions, such as appraising employee job performance, validating employee selection tests, evaluating jobs, planning career paths, and counseling individuals seeking vocational guidance. There are many practical benefits of grouping jobs effectively. For example, rather than having to develop distinct measures to assess employee performance for each individual job in an organization, job grouping can justify developing measures for a smaller set of job groups. Thus, grouping transforms a potentially cumbersome, costly, and time-consuming task into a more manageable, less expensive, and less time-consuming task that is, one hopes, just as useful. Of course, the practical benefit of reducing the total number of jobs to a manageable and appropriate number of job families depends on theoretical notions of generalizability, first that jobs can be aggregated into job families on characteristics that are relevant across jobs (versus those unique to jobs and job positions), and second that whatever unique information about jobs might be sacrificed through grouping jobs does not adversely affect the purposes to which the resulting job groups are put. Of course, unique job information can serve to supplement the organizing scheme provided by a job taxonomy.
职业信息网络(O *网)和标准职业分类(SOC)系统
职业信息网络(O*NET)成立于1998年,是劳工部计算机化的职业头衔词典(DOT)的替代品。O*NET旨在成为一个全面而灵活的分类系统,用于在美国针对与工作相关的活动,如就业测试、培训、补偿、招聘和职业教育和咨询的多个维度对工作进行分类。O*NET数据库不是使用交通部用来分类工作的“数据-人-事”框架,而是围绕一个名为“内容模型”的框架组织起来的,该框架包括六个广泛的领域,前三个是面向员工的,后三个是面向工作的:
- 工人要求(例如,基本技能,交叉功能技能,教育)
- 工人特征(例如,能力,兴趣,工作风格)
- 经验要求(例如,培训,经验,许可)
- 职业要求(例如,工作内容,组织环境)
- 职业特定信息(例如,特定于职业知识,技能,任务和工具和设备)
- 职业特征(例如,劳动力市场信息,工资)
从工作人员和监督员持续收集来自这两个主要领域的工人和工作特征的级别和重要性的评级,大多数数据被收集在相关的交叉工作特征上,与任务特定和工人特定的在点中发现的重点。研究了研究数据的可靠性,Interrade Angress,因子结构和有效性正在进行的研究。o *净系统使用标准职业分类系统(SOC),这是所有美国政府机构都在迁移的标准。
职业探索指南
职业探索指南(GOE),由美国就业服务处于1979年开发,是一种职业类型,从衡量职业兴趣的理性实证方法中产生,它仍然用于职业探索和职业咨询目的。利益框架包含12个因素,可以成对地分为荷兰RIASEC利益框架(现实的、调查的、艺术的、社会的、进取的和传统的利益)。在这个框架内的工作包含了大多数(如果不是所有的话)O*NET的工作;研究人员根据教育、体能、任务和情境等因素进一步将小组划分为66个小组;这些群体又进一步细分为348个亚群体。对于职业探索的目的,66组分类是GOE的主要重点,在那里能力概况(例如,从通用能力倾向测试,或GATB)和职业兴趣概况(例如,从荷兰RIASEC代码)可以分配到工作。这种工作分类可能比O*NET更侧重于理论,尽管O*NET包含一个交叉代码来将其职业数据结构到GOE框架中。职业能力倾向模式(OAP)地图根据能力要求(物理、官僚、社会、经济和艺术)将其划分为四大类,并划分为五个层次的一般认知能力要求,对GOE的工作分组进行了补充。能力和职业兴趣都符合OAP图。其他分类法也将理论兴趣和能力结构应用于职业结构。 The American College Testing (ACT) Program’s World-of-Work Map (which makes use of the Holland RIASEC structure) and the Minnesota Occupational Classification System III (MOCS-III, which inte-grates interests, ability, and motivational characteristics in matching individuals and jobs) are two major exemplars for the purpose of matching individuals to jobs in vocational counseling.
职业前景手册
The Occupational Outlook Handbook (OOH), first published in 1948 by the U.S. Bureau of Labor Statistics (BLS), is updated yearly and contains a wide range of occupational information, with jobs classified by SOC codes (similar to O*NET) and SOC codes comprising approximately 270 occupations that are grouped into 10 broad clusters: management, professional and related occupations, service, sales, administrative support, farming and related occupations, construction, installation and related occupations, production, and transportation, with additional discussion about careers in the U.S. armed forces. Each occupation contains seven major sections describing it:
- 工作的性质(例如,工作职责;行业和工作类型的责任水平)
- 工作条件(例如,工作时间;物理环境;级别的安全;所需旅费)
- 就业,培训,其他资格和进步(例如,培训类型和长度;所需的学位,许可或认证;继续教育需求)
- 工作前景(例如,预计的增长或下降;工作数量;工作竞争水平)
- 收益(例如,工人倾向于得到补偿,无论是由薪资,委员会还是奖金和提示;收入如何因经验和地理区域而变化;典型的好处)
- 相关职业
- 附加信息的来源(例如,对其他机构或组织,出版物和网站的推荐)
职业就业统计数据
职业就业统计(OES)也由BLS制定,是寻求有关收益详细信息的人的主要来源,因为OES从200,000个机构中分析了就业和工资的数据,在大约800个全日制和兼职的情况下抽样occupations (excluding farm-related) that represent the U.S. workforce. Occupations are organized into 22 groups by SOC code. Wages and employment levels are provided at the national, state, and metropolitan area levels; they are provided by hourly wage and annual wage, as well.
北美工业分类系统
除了OES和OOH, 1997年BLS还创建了北美行业分类系统(NAICS),作为标准行业分类(SIC)系统的更新替代品。顾名思义,NAICS是共同合作的产物,美国、加拿大和墨西哥(北美自由贸易协定的贸易国,北美自由贸易协定),和职业是按行业分组的方式反映了生产过程或相似之处是如何产生的,没有什么是:生产。多个美国政府机构在NAICS系统下收集和整理有关就业、工资、离职率和职业安全和健康的数据;系统独立于SOC,但显示出清晰和直接的联系。几个分类系统之间的联系可以从国家人行横道服务中心在线获得。
结论
职位分类,如O *网,GOE,欧洲核武器,允许许多重要的心理和情境因素,以显式和隐含地影响所产生的工作组。在人员选择和培训,工资赔偿和职业咨询等领域的研究人员和从业者可能希望密切关注他们选择的作业分类物 - 特别是作业团体的类型和狭窄或广度 - 因为分类案可以选择对由他们产生的决定具有重要影响。
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