Trend 2003 - 2014. National Center for Education Statistics. Graduation Rates - All Students at Postsecondary Schools: Student Population | Country: USA | State: New Jersey | Institutions by State: Rutgers University-New Brunswick | Gender: All Genders | Race: All Races/Ethnicities, 2003-2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 017-012-001.
Bibliographic record
Abstract
National Center for Education Statistics (2017). Graduation Rates - All Students at Postsecondary Schools: Student Population | Country: USA | State: New Jersey | Institutions by State: Rutgers University-New Brunswick | Gender: All Genders | Race: All Races/Ethnicities, . Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 017-012-001. Dataset: Reports a count of the cohort of students who enrolled in a 4-year institution 6 years prior to the year shown. Totals exclude those who died or were disabled; and those who left school to serve in the armed forces or serve on some other official mission (eg, Peace Corps, church mission). The data are use to calculate the graduation rate. This dataset covers graduation rates at 4-year colleges and universities. The rate reflects the percent of students who completed their degrees within six years of first enrollment. Data are from the Integrated Postsecondary Education Data System (IPEDS) conducted by the NCES. IPEDS involves annual institution-level data collections. All postsecondary institutions that participate in federal programs providing financial assistance to students are required to report data using a web-based data collection system. Integrated Postsecondary Education Data System (IPEDS) datasets are labeled using a two-year notation specifying the start year and the end year and data files are exported by start year: for example, the 2006-2007 school year noted as 2006 represents enrollment 2006-2007. Also note that odd years or even years refer to the time period being referenced, not the year in which the data are collected: for example, during the 2011-2012 data collection, fall enrollment in 2011 (odd year) is collected in spring 2012. For information on the statistical standards utilized by the National Center for Education Statistics (NCES), visit http://nces.ed.gov/statprog/index.asp . Also see About US Higher Education Statistics at http://data-planet.libguides.com/UShighered Category: Education Source: National Center for Education Statistics The National Center for Education Statistics (NCES) is the primary federal entity in the United States for collecting and analyzing data related to education in the US and other nations. NCES is located within the US Department of Education and the Institute of Education Sciences. The NCES fulfills a congressional mandate to collect, collate, analyze, and report complete statistics on the condition of US education; conduct and publish reports; and review and report on education activities internationally. The NCES is one of four centers (along with the National Center for Education Research, the National Center for Education Evaluation and Regional Assistance, and the National Center for Special Education Research) charged with carrying out the work of the Institute of Education Sciences. http://nces.ed.gov/ Subject: Higher Education, Undergraduate Students, College Enrollment
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.020 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.074 | 0.084 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".