Lost in (the Business of) Translation: Invest in the Youth
Notice bibliographique
Résumé
To the Editor: Tom Curran produced a delightful article on “translational research” (1). Identifying problems in our current strategies to combat cancer may lead to positive changes. Dr. Curran mentions that “instead of rewarding teamwork, we teach competition and suspicion and we create barriers to collaboration” and that “we need to encourage teamwork, cooperation, and open communication.” Under the current system of funding and rewarding achievements, this wish cannot be fulfilled. How could a postdoc, working in a mega-lab with 30 to 40 others, hoping to get a paper in a high-profile journal, be cooperative and collaborative? Not a chance!The way the current system works, it seems that as scientists become more successful, their chances to “cure cancer” are decreased. Those who devoted their life to cancer research started with a dream of finding a cure. This enthusiasm is progressively eroded as one gets more successful and enjoys the associated rewards. The “dream” is slowly transformed into a “business” with goals that are not necessarily focused on “cures.” In my opinion, the problem is that as success increases, quality time for creative thinking, reading literature, spending time in the lab, etc., decreases. It goes like this, you publish good work, you get more invitations to speak, fly a lot, write more papers, apply for more grants, receive requests for consultation in exchange for money and stock, become Associate Editor of prestigious journals, reviewer of grants, participate in committees, and on it goes.Once your lab hits 20 to 30 people, you do not remember their names. Incoming journals stay unopened for weeks and you have no time to answer your e-mails. At the end, you meet with your students in the corridor. Your name can attract mega-projects and millions of dollars. You hire professional grant writers, “second-in-command,” etc. At the end, you become a “celebrity” and have your own company. You have too much to think of in the morning and finding a cancer cure becomes a detail. Celebrity status can still get you large grants and papers, but you may not know exactly what they say.Why aren't too many young people are interested to follow a research career? Those who are exposed to science as undergraduate and graduate students realize that this is a tough and very competitive profession. Striving to publish articles and obtain grants and getting early slaps in the face is no fun. I have heard complaints from M.D. to Ph.D. students that their much needed imagination is entrapped very early in their careers by trying to get fast results and publications, that, they hope, will help them to get grants.How could we have hopes that cancer patients will get better treatments in the future? One solution is for granting agencies and associated bodies to focus on the youth. Here are some suggestions:Investing in youth will bring in many more bright minds into science. Along with them will come new ideas and approaches and, likely, more innovative cancer cures. Although the necessity of funding mega-projects and mega-centers is not questioned, the brightest ideas are likely to come from individual gifted minds who have time to think, not from frequent flyers and busy celebrities.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,067 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,010 | 0,008 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,014 | 0,016 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,008 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».