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Record W326405722

Teaching Math to the Talented: Which Countries-And States-Are Producing High-Achieving Students?

2011· article· en· W326405722 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEducation next · 2011
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Programs
Canadian institutionsnot available
Fundersnot available
KeywordsMedalMathematics educationGold medalTest (biology)Class (philosophy)Political scienceProductivityPsychologyMathematicsEconomic growthGeographyComputer scienceEconomicsHistory
DOInot available

Abstract

fetched live from OpenAlex

In Vancouver last Winter, the United States proved its competitive spirit by winning more medals--gold, silver, and bronze--at the Winter Olympic Games than any other country, although the German member of our research team insists on pointing out that Canada and Germany both won more gold medals than the United States. But if there is some dispute about which Olympic medals to count, there is no question about American math performance: the United States does not deserve even a paper medal. Maintaining our productivity as a nation depends importantly on developing a highly qualified cadre of scientists, engineers, entrepreneurs, and other professionals. To realize that objective requires a system of schooling that produces students with advanced math and science skills. To see how well schools in the United States do at producing high-achieving math students, we compared the percentage of U.S. students in the high-school graduating Class of 2009 with advanced skills in mathematics to percentages of similarly high achievers in other countries. Unfortunately, we found that the percentage of students in the U.S. Class of 2009 who were highly accomplished in math is well below that of most countries with which the United States generally compares itself. No fewer than 30 of the 56 other countries that participated in the Program for International Student Assessment (PISA) math test, including most of the world's industrialized nations, had a larger percentage of students who scored at the international equivalent of the advanced level on our own National Assessment of Educational Progress (NAEP) tests. Moreover, while the percentage of students scoring at the advanced level on NAEP varies considerably among the 50 states, not even the best state does well in international comparison. A 2005 report from the National Academy of Sciences, Rising Above the Gathering Storm, succinctly put the issue into perspective: Although many people assume that the United States will always be a world leader in science and technology, this may not continue to be the case inasmuch as great minds and ideas exist throughout the world. Demand for High Achievers gap between the burgeoning business demand for a highly accomplished workforce and a lagging education system has steadily widened. Even as the United States was struggling with a near 10 percent unemployment rate in the summer of 2010, businesses complained that they could not find workers with needed skills. New York Times writer Motoko Rich explained, The problem ... is a mismatch between the kind of skilled workers needed and the ranks of the unemployed. Skill shortages have severe consequences for a nation's overall productivity. Two of the authors of this report have shown elsewhere that countries with students who perform at higher levels in math and science show larger rates of in economic productivity than do otherwise similar countries with lower-performing students (see and Economic Growth, research, Spring 2008). Public discourse has tended to focus on the need to address low achievement, particularly among disadvantaged students. Both federal funding and the accountability elements of No Child Left Behind (NCLB) have stressed the importance of bringing every student up to a minimum level of proficiency. As great as this need may be, there is no less need to lift more students, no matter their socioeconomic background, to high levels of educational accomplishment. In 2006, the Science, Technology, Engineering, and Mathematics (STEM) Education Coalition was formed to raise awareness in Congress, the Administration, and other organizations about the critical role that STEM education plays in enabling the U.S. to remain the economic and technological leader of the global marketplace for the 21st Century. In the words of a National Academy of Sciences report that jump-started the coalition's formation, the nation needs to increase its talent pool by improving K-12 science and mathematics education. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.351
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it