Notice bibliographique
Résumé
Careers for Kids! How to Help Your Kids Choose a Career, by Robert Shewchuk. 2013. Winnipeg, Manitoba, Canada: Start Smart Publishing. 157 Pages. Paper. $14.95 CDNThe subtitle of this book is How to Help Your Kids Chose a and it is clearly aimed at parents wanting to help their teens select potential careers suited to their skills, gifts, and interests. This book's chatty, conversational style puts the reader at ease immediately, assuring us you don't have to be a Counselor with years of training and experience to help guide your child through the labyrinth of career exploration. I am a big fan of how this book is organized. Visually, it is a very easy read with plenty of white space on each page, and Mr. Shewchuk has kept this book to a manageable 157 pages. Further, its information has been precisely categorized. There are seven chapters arranged to address each progressive step of career planning, none of them lengthy, and all of them packed solid with current career exploration practices combined with ideas, suggestions, and personal stories.Careers for Kids could have been a hard sell, considering the training, education, and hands-on experience career counsellors are expected to accumulate to do theirjob well. However, Mr. Shewchuk is able to provide enough solid background in basic career exploration that parents can feel they come to this project with a understanding of what is required of both themselves and their teen. For example, he uses the visual of Old Linear vs. New Zig Zag as a model to identify the pattern of career paths in the 21st century compared to those of thirty years ago, and with which most parents would be more familiar. He then introduces the concept of how Labor Market trends work, illustrating as a case in point, how technology has motivated the decline in watch-wearing now that most people have cell phones. His invented phrases are fun and engaging. He uses Career Mashers to describe mixing several interests together to mash a new career, such as a writer passionate about the environment. Another example is Career Moochers which describes discovering support roles in trending sectors such as technology even if one is not tech-savvy.The process of elimination, personality metrics, the making of lists, and research plans are all typical of most career exploration processes. Mr. Shewchuk offers them in such a concise and defined blueprint - including steps on keeping your youth motivated, and suggestions for exploring options within the broader categories such as education and health - that I can see how this would be an enjoyable, informative, and engaging project for both parents and teens. There are some recurring suggestions in the book that repetitive work, manual labour and retail jobs are perhaps not the good jobs to which to aspire.However, in my own career as an Employment Counselor, I have met retail associates and hospitality servers whose passion is delivering superb customer service, and they have honed their craft to such an art that they are actively sought out in their sectors by employers and recruiters. …
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,072 | 0,067 |
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 ».