Bibliographic record
Abstract
There is a well-rehearsed argument that we are fast approaching a digital divide, of users and non-users of the Internet (Wang et al., 2011). Moreover, the low use of the Internet by older people has been described as a ‘grey digital divide’ (Millward, 2003). This may be explained by the fact that many retired people today lived the majority of their lives without the Internet. However, writing this chapter in 2012, it is apparent that older people are making the digital conversion in ever increasing numbers. It is estimated that around 40 per cent of people aged 65+ use the Internet across industrialized countries, with figures ranging from 38 per cent in Sweden and 39 per cent in New Zealand (Centre for Digital Future, 2009), to 41 per cent in the United Kingdom (Ofcom, 2010), 42 per cent for the United States and 45 per cent in Canada (Centre for Digital Future, 2009). Moreover, older people are the fastest growing segment of Internet users, as numbers of younger age groups appear to plateau (ABS, 2005). Data from the United Kingdom show that older people use the Internet in similar ways to younger age groups (ONS, 2011). There is also evidence to suggest that older people join online support groups (Pfeil and Zaphiris, 2009) and that the volume of such interaction is steadily increasing (Nimrod, 2009).
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".