CREAT: Census Research Exploration and Analysis Tool

The Management and Organizational Practices Survey (MOPS): Cognitive Testing*

January 2016

Working Paper Number:

CES-16-53

Abstract

All Census Bureau surveys must meet quality standards before they can be sent to the public for data collection. This paper outlines the pretesting process that was used to ensure that the Management and Organizational Practices Survey (MOPS) met those standards. The MOPS is the first large survey of management practices at U.S. manufacturing establishments. The first wave of the MOPS, issued for reference year 2010, was subject to internal expert review and two rounds of cognitive interviews. The results of this pretesting were used to make significant changes to the MOPS instrument and ensure that quality data was collected. The second wave of the MOPS, featuring new questions on data in decision making (DDD) and uncertainty and issued for reference year 2015, was subject to two rounds of cognitive interviews and a round of usability testing. This paper illustrates the effort undertaken by the Census Bureau to ensure that all surveys released into the field are of high quality and provides insight into how respondents interpret the MOPS questionnaire for those looking to utilize the MOPS data.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
report, data, manufacturing, respondent, survey, organizational, reporting, management, performance, sample, census survey

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations.
:
National Science Foundation, Annual Survey of Manufactures, Center for Economic Studies, National Bureau of Economic Research, Federal Reserve Bank, University of Chicago, Census Bureau Center for Economic Studies, Michigan Institute for Teaching and Research in Economics, North American Industry Classification System, Business Register, Sloan Foundation, University of Toronto, Kauffman Foundation, Probability Density Function, Stanford University, Management and Organizational Practices Survey

Similar Working Papers Similarity between working papers are determined by an unsupervised neural network model know as Doc2Vec.

Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the capture of semantic meaning in a way that relates to the context of words within the document. The model learns to associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as document classification, clustering, and similarity detection by preserving the order and structure of words. The document vectors are compared using cosine similarity/distance to determine the most similar working papers. Papers identified with 🔥 are in the top 20% of similarity.

The 10 most similar working papers to the working paper 'The Management and Organizational Practices Survey (MOPS): Cognitive Testing*' are listed below in order of similarity.