Notice bibliographique
Résumé
The term ageism, coined by Robert N. Butler (1969), refers to the stereotyping of and prejudice against individuals or groups based on their age.According to Todd Nelson (2005), there has been little study and research on ageism as a form of prejudice, compared to racism and gender bias.As the baby boom generation (those born in Canada and the U.S. between 1946 and 1966) starts to consider retirement, it is about to come face to face with ageism on a scale never seen before.Within the next five years, North America is about to go from an unusually low number of people entering yearly into the "normal" retirement age of 65 to the highest number in history.Charles Longino refers to it as apocalyptic demography or the demographic imperative (2005, p. 80).There are growing concerns that the baby boomers could bankrupt the social support systems as they stand now.While all of this is taking place, older people are staying healthier and living longer than ever before.In addition to references to Nelson and Butler, this paper also refers to two recent psychology research papers which challenge previously held theories on aging, memory, and learning.Finally, it suggests a Friereian educational lens through which baby boomers could look to seek a significant role for themselves in raising the awareness of ageism as a form of oppression and to create the means to reverse its effects on everyone affected by it, not just older persons.In this paper I will be discussing several issues related to ageism.Certain defined age brackets will be assigned to terms and expressions.For instance, I will refer to people over the age of 65 to 74 as 'seniors', and people over 75 to as 'elders' and 'the elderly'.The terms 'baby boom' and 'baby boomers' will refer to the 20 year period following the end of World War II and those members of North American society born during that time.Although I consider the two age brackets to be totally stereotypical and arbitrary categorizations, and the 'baby boom' time frame to vary slightly between American and Canadian contexts, they have generally been accepted in popular use by government, the private sector, and the public at large.Keywords ageism, baby boom, demographic imperative, lifelong learning "The baby boom is on our doorstep.Is this the calm before the storm?We fear that it will be like a wrecking ball unleashing its destructive potential.However, it may be more like a challenge.Challenges can generate creative answers, many of which are unknowable ahead of time . . .We should embrace the challenge . . .(Charles Longino, Jr., The Future of Ageism: Baby Boomers at the Doorstep, 2005, p.83)Although prejudice based on age can be experienced by a member of any age group, I will be concentrating in this paper on ageism as it applies to the aging adult population, and in particular to those of the cohort referred to as the baby boom
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,001 |
| Communication savante | 0,004 | 0,006 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,135 | 0,032 |
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 ».