Lauching Geographic Education in to the 21st Century : The View from the United States.
Bibliographic record
Abstract
Geographic education in the United States has experienced an unprecedented resurgence in the schools during the past two decades. There are several compelling reasons for a revival of the discipline, among them a thoroughly documented level of geographic illiteracy in the school age population that raised the ire of politicians, parents, and geographers alike (The Gallop Organization, 1988). This paper discusses the way that educational reform has addressed the problems facing geographic education on the eve of the new millennium. A successful approach to the issues necessitated being able to move geography education forward in three phases. They were: 1) awareness of the problems facing the discipline; 2) the development of rigorous content standards to guide geography education nationally, and 3) national and state assessments of student performance in geography and teacher preparation initiatives. The significance of each of the three phases is discussed within the context of geographic education within the United States.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".