MétaCan
Menu
Back to cohort
Record W2099818270 · doi:10.1242/jcs.115.7.1341

Giving science in schools a sporting chance

2002· article· en· W2099818270 on OpenAlexaboutno aff
Caveman

Bibliographic record

VenueJournal of Cell Science · 2002
Typearticle
Languageen
FieldPsychology
TopicScience Education and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyNewspaperTest (biology)State (computer science)Library scienceMedia studiesEcologySociologyMathematics

Abstract

fetched live from OpenAlex

I read in a newspaper the following statistics. (1) California has the highest number of Nobel Laureates in the sciences of any US state and more than any country in the world. (2) Test scores for California school children(10-15 years old) in the sciences are the lowest of any US state and are considerably (and consistently) below those of children in Japan and Europe.How is it that an American state apparently rich in science talent (if a Nobel Prize is a mark of talent?) has such a dismal record of achievement in the sciences in children? Surely, one would expect some sort of trickle-down effect in which the local greats in science are held up as examples to children, who, in turn, look up to them and are inspired. Assuming that test scores are a reflection of future creativity at the bench (a big assumption),these children will not, apparently, be the next generation of the science elite - at least in California.In sports, this would not be the case: excellence of individuals in a given sport would correlate directly with excellence of youth in that sport. For example, recall the amazing increase in the number of Swedish tennis players and their rise to prominence after the success of Bjorn Borg, or the desire of the basketballing youth in America to be “just like Mike” when Michael Jordon was in his prime. One could reiterate this point for most sports - soccer in South America, rugby in New Zealand, ice hockey in Canada,cricket in England - no wait a minute, that's going to far! But, what about the sciences? Do the youth look up to Nobel Laureates or the common-or-garden form of scientist that is most of us? Where and when does the layperson have the chance to see a scientist `au naturel', someone to emulate, someone who is interesting and doing something that they would like to excel at and be recognized for?We constantly see sports stars on television, in films and magazines. But,where are the prominent scientists? Where are the person's interest stories(Fiona Watt's secret life as a Scottish reggae bongo player), the full-color spreads in magazines (Günther Blobel modeling spring fashions for the discerning cell biologist), interviews on day-time TV (Paul Nurse's favorite sponge cake recipes) or endorsements for products in advertisements (why Gary Borisy prefers boxers)? This is where the general public, and particularly those under 18, is most influenced.But before you go out and endorse PG Tips and Marmite as the reasons for your success in science, there are more obvious and direct ways to promote science in schools.Funding is one. Again, the comparison with sports is telling. All of us can identify in one sport or another the player who was signed for millions, the stadium that was built for hundreds of millions, the millions spent on training and facilities, and the role of national/local governments in contributing (your taxes) to these ventures. When did you (last) hear about such investments in science education in our schools? Probably never. Why are national and local governments allowed to make these `investments'? Be an advocate for funding of science in schools, champion those in local government that want to fund schools and oppose those who divert precious resources to sports stadiums. Go to fund-raisers for your school, get involved in parent associations and talk to school administrators and teachers.Involvement in teaching and training is another way to promote science in schools. There are several ways to do this. Volunteer to teach science in your local school. I find that teachers are happy for some `spot' help, as long as you are respectful of their work and time. Run clubs (e.g. a math club),although this is usually outside of regular school hours. I have had several graduate students who have given lectures in local high schools - and in one case taught full time while completing the final year of her PhD! Get involved in training. For example, design short courses for science teachers to teach them new techniques and simple experiments - it is amazing how sophisticated the experiments can be (cloning genes into bacteria, analysis of protein distributions by microscopy). These experiments should be transplantable to the school science lab. What about equipment? I am sure that your lab, like mine, is full of old pieces of equipment in storage that are in sufficiently good working order for a school lab.Another target of training in your lab is the student. Such training can be in the form of group summer projects. In my institution, we have several summer programs for high-school students (usually in their penultimate or final year). There is a selection process for applicants, and the successful ones are matched, usually in pairs, with different labs. They work on a specific project for six weeks, supervised by the head of the lab and a postdoc or senior graduate student. At the end there is either an oral presentation or poster session, where the students present their work - it has not been uncommon for the students to be included as a co-author on a subsequent publication. The ultimate involvement is to have a solo high school student in your lab. Some homework is required of you to make sure that they have the potential to learn techniques and to handle lab personalities,although these may be close to the adolescent, sophomoric state in schools(the one that I have in my lab is brilliant).In reality, direct contact with school science teachers and students is the best and probably only way both to raise the visibility of scientists and their profession to students and to improve the quality of science in schools. However, scientists should not pass up the opportunity to advertise to the general public, even if you have to wear paisley boxers and the timing of your bongo rhythm is off!

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.122
Threshold uncertainty score0.407

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0090.004
Scholarly communication0.0130.010
Open science0.0010.008
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.1220.040

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 head0.072
GPT teacher head0.389
Teacher spread0.318 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cell ScienceSame topicScience Education and PerceptionsFrench-language works237,207