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Protecting and Accessing Data from the Survey of Earned Doctorates A Workshop Summary (2010) / Chapter Skim
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3 National Science Foundation Options, Decision, and Impact
Pages 15-26

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From page 15...
... A BALANCING ACT The objective of the NSF strategy for disclosure protection, according to Stephen Cohen, is to balance data utility and disclosure risk. As NSF tries to make the data more useful and accessible to data users, the risk of disclosure of confidential information also tends to increase (see Figure 3-1)
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From page 16...
... , sources of financial support during graduate school, and salary of next position. Because the individual responses are protected by NSF and the contracted collection organization, the National Opinion Research Center (NORC)
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From page 17...
... In response to a question, Cohen stated that the decision to suppress the data was preemptive; that is, there had been no complaints about the old policy that resulted in publication of fine field cells, but the agency had received undocumented feedback from users of other NSF surveys that there were concerns about the potential for disclosure of confidential information. The publication of the suppressed 2006 REG tables and 2006 Interagency Summary Report generated a strong negative response from the SED data user community concerning diminished access to information about underrepresented minorities.
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From page 18...
... NSF reissued the 2006 Interagency Summary Report and 2006 REG tables using its earlier level of confidentiality protection, acknowledging that the user community had not been notified or involved in discussions of changes in the release of the 2006 data. The agency also set about to explore alternative disclosure protection strategies that would maximize the reporting of REG data and simultaneously meet the requirements of protecting the confidentiality of information provided by respondents.
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From page 19...
... Controlled rounding, in which the values of individual data cells in a statistical table are altered, again without affecting the marginal totals in the table, is another perturbation scheme. NSF did not consider data perturbation a viable option because of the interest of some SED data users in tracking small cells of race/ethnicity data; precision of the data in small cells is very important to these users.
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From page 20...
... DATA PROTECTION STRATEGY Mark Fiegener, SED survey manager, discussed the strategy that, after consideration of user feedback, SRS finally adopted. The chosen option switches the focus of the disclosure protection strategy from suppression based on counts in individual cells to counts in domains -- in this case, field of degree.
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From page 21...
... Likewise, fields of degree in which fewer than  doctorates are awarded in a given year will not be displayed separately; they will be aggregated for that year in all REG tables with "related" fine fields, so that degree counts in combined fields are at least 25. The selection of a cutoff point of 25 was questioned by workshop participants.
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From page 22...
... Aggregation Rule 3: When a single below-threshold fine field does not share a 4-digit CIP code with any other below- or above-threshold fine field, aggregate the degree count from the below-threshold fine field with the appropriate "other fields" category within the same major field. Aggregation Rule 4: When multiple below-threshold fine fields do not share 4-digit CIP codes with any other below- or above-threshold fine fields, and the total of the degree counts exceeds the minimum count plans to reassess the fine fields selected for aggregation on a 3-year cycle.
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From page 23...
... Fiegener mentioned several illustrative tabulations to show the impact of applying the various rules. An example was given applying Aggregation Rule #1: When two or more below-threshold fine fields share a 4-digit CIP code, aggregate the degree counts from these fine fields into one or more aggregated fields that have above-threshold degree counts in Table 1a of the SED published tables for 2006.
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From page 24...
... Citizens and Permanent Residents 1997 1998 1999 2000 Agricultural sciences/natural resources 700 676 635 621 Forest engineering 4 1 0 2 Forest sciences & biology 19 13 7 14 Forest/resources management 15 18 13 7 Forestry & related science, other 31 41 29 34 Horticultural science 25 30 25 23 Natural resources/conservation 12 16 18 13 Plant pathology/phytopathology 32 28 25 29 Poultry science 5 2 2 6 Plant sciences, other 12 14 14 19 Soil chemistry/microbiology 21 12 18 19 Soil sciences, other 27 43 36 28 Wildlife/range management 41 45 35 44 Wood science & pulp/paper technology 14 10 9 2 Agriculture general 3 4 6 5 Agricultural sciences, other 15 19 19 17 NOTE: CIP = Classification of Instructional Programs; see text for explanation of shaded text; and na = doctorate degree not offered in this field in this year. SOURCE: National Science Foundation/National Institutes of Health/National an explosion in Ph.D.s in a fine field in a year following a year in which there were too few to warrant separate publication, the year in which the 25 threshold was met would be published.
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From page 25...
... In fact, in that same year, there was one field of study -- art education -- in which 11 or fewer institutions offered doctorate degrees; 9 of the 25 art education doctoral degrees were awarded by just one institution. In these special cases, NSF plans to provide detailed published notes regarding the aggregation decisions to inform data users.
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From page 26...
... Again, to assist users, NSF plans to publish detailed notes outlining the reason for the elimination of data series.
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Key Terms

  • fine field
  • degree counts
  • aggregation rule
  • reg tables
  • sed data

  • data cells
  • earned doctorates
  • cip code
  • summary report
  • data users

  • degree count
  • disclosure protection
  • data suppression
  • aggregation rules
  • confidential information

  • disclosure risk
  • protection strategy
  • user community
  • interagency summary
  • doctorate recipients

  • data protection
  • individual data
  • data user
  • data perturbation
  • data series

  • cip aggregation
  • data utility
  • degree using
  • disclosure limitation
  • aggregated fields


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