Notice bibliographique
Résumé
Vermond, Kira. The Secret Life of Money: A Kid’s Guide to Cash. Illus. Clayton Hanmer. Toronto: Owl Kids, 2012. Print. As a kid, I learned about money early from a banker father, an entrepreneurial great-aunt, a compulsory grade 9 consumer education class, and high school elective in economics. This book amalgamates all those types of sources in a great introduction for kids, parents, and adults alike. It is written in a breezy style with clever phrasing, illustrations, variation in presentation format, and is peppered with quotes from the likes of Groucho Marx, ABBA, and Maya Angelou. Although written by a Canadian with many Canadian examples, there is a distinct American flavour in the spelling (ex. paycheck vs. paycheque), green colour scheme, and choice of pithy quotations. Three main themes emerge: what is money, how to get it, and how to keep and grow it. The chapter on the history and nature of money has some great examples of “wacky” forms of cash used throughout history. There is, however, little if anything about world currencies today. Vermond confronts the many problems with the expectations or hopes of “free” money (ex. lottery winnings, stealing, counterfeiting, scams and frauds) and guides the reader towards developing good long-term habits, realistic wage and salary expectations, and the importance of ongoing learning about saving and growing money through investing and compound interest. For example, few of us will make millions as CEOs or sports stars so benchmarks such as $7.25 per hour as a busboy or $45,000 as a firefighter are more realistic. The examples of how kids can earn money seem a bit standard (ex. mow lawns, babysit, paper route, deliver goods to old people) but I suppose opportunities for youth don’t change much. There is lots of discussion on how to keep your hard-earned money including smart spending, the pros and cons of credit as well as references to interesting research in behavioural economics, advertising shenanigans, and the cost of being cool. I especially appreciate the author’s willingness to tackle social justice issues. She introduces some research on the social value of various careers (ex. advertising managers ‘waste’ $17 for every dollar they earn while hospital cleaners ‘create’ $15). There is also coverage of microcredit, societal costs of poverty, causes of the gaps between rich and broke countries, unintended consequences of donating old clothing to charity, consumerism vs. consumption, and even the notion that salary satisfaction is all relative. The overall message seems to be that media-inspired dreams of mansions and pools are unrealistic so hard work and life-long learning about money is required. Fortunately, work also contributes to our overall life-satisfaction. Recommended: 3 out of 4 starsReviewer: David SulzDavid is a Public Services Librarian at University of Alberta and liaison librarian to Economics, Religious Studies, and Social Work. He has university studies in Library Studies, History, Elementary Education, Japanese, and Economics; he formerly taught in schools and museums. His interests include physical activity, music, home improvements, and above all, things Japanese.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,089 | 0,054 |
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 ».