Sentence examples for discipline data from inspiring English sources

The four introductions range in length from 33 to 82 clauses and are introduced in Table 2: Table 2 Data set and number of clauses Discipline Data set Number of ranking clauses Chemistry Brooks et al. (2013) 59 Kennedy et al. (2013) 32 History Bowen (2010) 31 Patrick (2011) 54   TOTAL 176.

The researcher examined the BON's discipline data bank for the years 2002 through 2012 to find specific violations that were likely to lead to multiple disciplinary actions.

Student discipline data illustrates an implicit bias.

Latinos and students with disabilities were also overrepresented in the discipline data.

Researchers from American University and University of California, Davis, looked at teacher demographic and student discipline data for North Carolina elementary school students from 2008 to 2013.

In a 2011 voluntary agreement with the U.S. Education Department, the district pledged to track and report discipline data and eliminate inequitable practices.

While such systems allow individual departments to customize data collection to the needs of individual disciplines, data sharing between departments, schools and universities became hindered.

Improved watershed modeling as applied to nutrient loss and water quality issues affords both challenges and opportunities for hydropedology if scientists are willing to bridge disciplines, data, and scales to address current limitations.

His career success reflects the changing nature of campaigns, in which swashbuckling strategists are becoming less of an asset than disciplined data nerds who can build a loyal and effective campaign operation the way a seasoned Silicon Valley entrepreneur might.

Finally, there is currently broad interest in cross-discipline data linking, partly stimulated by government initiatives to make raw data available to encourage the development of new analysis and services to improve society [ 62].

In other disciplines data mining has been used to classify dangerous parts of Brazilian cities, where useful information was found by employing decision trees for the attributes related to a particular characteristic such as infrastructure conditions, hydrology, soil, recreation area, community characteristics, among others.