Bibliographic record
Abstract
This project serves as a follow-up to an earlier report presented at the annual meeting of the American Educational Research Association -Montreal, Canada in April 1999 (Nichols, Ludwin, & Iadicola, 1999) in which the student discipline and suspension data for a large urban school corporation in the Midwest were explored. In the earlier project, flawed data collection procedures by the school corporation made analysis of the data tentative and problematic. As a result, new data collection procedures were implemented the year. This project explores this following data and expands the analysis to include data from six high schools, 11 middle schools, and 35 elementary schools. Analysis of the student discipline data is presented with a discussion centering on the overrepresentation of minority and low-income students within the data. In addition, this project includes a discipline consequence and zone analysis of behavioral occurrences. Implications for future research are also discussed. Since the inception of the Gallop Poll of the Public's Attitudes Toward the Public Schools in 1969, classroom management and school discipline issues have been the public's primary educational concern on 16 occasions. It is clear that poor student behavior impedes learning and student achievement, and sets the stage for an ineffective educational environment and community. The seventh goal of the National Education Goals states that by the year 2000, [all schools in America] will be free from drugs and violence and the unauthorized presence of firearms and alcohol, and offer a disciplined environment that is conducive to learning. (Goals 2000: Educate America Act, 1994, §102) To accomplish this goal, the Safe and Drug-Free Schools and Communities Act of 1994 provides for support of drug and violence prevention programs. Additionally, this act includes an impact evaluation component, which contains a provision that requires the National Center for Education Statistics (NCES) to collect data to determine the frequency, seriousness, and incidence of student misbehavior and violence in elementary and secondary schools. Although on a national level these efforts may be seen as promising in their effort to improve the educational environment, locally many schools are making more tangible efforts in support of programs and documentation to address these issues. In addition, discussion in educational circles continues to center around the fair and appropriate distribution of discipline consequences to all students. These efforts allow discussion to focus on the disproportionate number of misbehavior incidents among minority students. Included in these discussions are the disparity of discipline consequences that may occur among ethnic majority and minority offenders and their designated economic status (free or reduced lunch status) in the public school setting. LITERATURE REVIEW It is not feasible to compile a list of all possible factors that precipitate student misbehavior in the classroom with an even greater task to address the variety of techniques and consequences that may be implemented as possible solutions to problem behavior. Mansfield, Alexander, and Farris (1991) observed that 44% of teachers nationwide reported that student misbehavior interfered substantially with their attempts to teach their material on a daily basis. In a recent meta-analysis of factors influencing student learning, teachers' skills in their ability to manage student behavior was identified as the most important (Wang, Haertel, & Walberg, 1993). In a 1987 study for the National Center for Education Statistics, 44% of public school teachers reported more disruptive classroom behavior in their schools than five years earlier (NCES, 2004). Although programs similar to Gateway (Davis, 1994), Central Park East (Scherer, 1994), and ALPHA (Abbott, 1994) offer unique organizational and curricular structures in their attempt to effectively address at-risk students in danger of school failure and/or those with multiple misbehavior or discipline incidences, limited empirical evidence exists to suggest program effectiveness. …
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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 | 0.019 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".