Minimizing the cost of your veterinary education: Saving through expedited student debt repayment.
Notice bibliographique
Résumé
In recent months, the issue of student debt has been at the forefront of many discussions within the veterinary community. Economists with the American Veterinary Medical Association (AVMA) have gone so far as to question the return on investment on a veterinary education, given that the average debt load that American veterinary students graduate with has reached $135 000 (1). In Canada, we are fortunate to typically have substantially lower tuition fees compared to our colleagues south of the border. That being said, many students in this country still graduate with significant debt. During the fall season of 2015, the Canadian Veterinary Medical Association’s Business Management Program partnered with the respective provincial veterinary medical associations to commission a Survey of Compensation and Benefits for Associate Veterinarians within each province. While the primary purpose of this survey was to gather information on compensation, hours worked, and benefits for associate veterinarians, a number of questions relating to student debt were also asked. In order to standardize the population examined, only data from those respondents who attended a Canadian veterinary college, and paid domestic student tuition, were included in this analysis. According to the 2015 provincial associate surveys, 75% of Canadian veterinary college graduates between 2013 and 2015 graduated with student debt. Of those with debt, the median owed ranged from $40 000 to $65 000. The median debt of all graduates from 2013 to 2015 was $51 500 (Table 1). Table 1 Median student debt of domestic students at graduation from Canadian veterinary colleges, stratified by year of graduation The median annual compensation of all graduates from 2013 to 2015, employed as associate veterinarians, was $71 000. The Canada Revenue Agency (CRA) Payroll Deduction Calculator allows us to accurately estimate a monthly net income (after taxes and deductions) from this median figure for annual compensation (2). Using an annual compensation of $71 000, monthly net income ranges from $4022 to $4368, depending on the province of employment. Assuming a repayment of $600 (14% to 15% of median net income) and an interest rate of 3.7% [as is currently being advertised by Canadian financial intuitions for veterinary student lines of credit (3)], a recent veterinary graduate paying down their debt of $51 500 can expect to have it paid off after 8.3 years. Holding debt for this amount of time will cost these graduates almost $8500 in interest (Table 2). Table 2 Time required and interest paid on $51 500 stratified by monthly repayment amount By increasing monthly student loan payments by 50%, recent veterinary graduates can save meaningfully on the interest they pay over the course of holding their debt. Paying $900 (21% to 22% of median net income) a month would reduce the time required to pay off a $51 500 student loan to just over 5 years, with approximately $5200 paid in interest. This results in saving more than $3100. By being even more aggressive and increasing monthly repayment to 100% above the original figure of $600, recent veterinary graduates can earn themselves greater savings. Committing $1200 (27% to 29% of median net income) each month towards paying down a $51 500 student loan, the debt can be erased in less than 4 years, and cost under $4000 in interest; a savings of over $4500. Dedicating $1200 towards paying down student debt can be a manageable target to strive for, especially with a median monthly net income of over $4000. It will necessitate frugality in other areas, but the payoff in saved interest makes it a worthwhile goal. The added bonus is the mental satisfaction that many people realize from being debt-free. For many of Canada’s veterinary students, student debt is necessary in achieving their educational goals. By taking an aggressive approach to paying down this debt after graduation, it is possible to save over $4500 in interest payments. Better to keep this $4500 for oneself, rather than handing it over to financial institutions, simply for the privilege of staying indebted for longer.
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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 | 0,003 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,004 |
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 ».