Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it