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2006· article· en· W4239671045 on OpenAlexaboutno aff
Jackie Jenkins

Bibliographic record

VenueAustralasian Journal on Ageing · 2006
Typearticle
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Everyday lifeSociologyThe InternetAgeing societyPsychologyInternet privacyEngineering ethicsPublic relationsGerontologyPolitical scienceComputer scienceEngineeringHistoryWorld Wide WebMedicineLaw

Abstract

fetched live from OpenAlex

Impact of technology on successful aging N. Charness and K. Warner Schaie (eds) . New York : Springer , 2003 . ISBN 0-826-12403-8 (hard cover). $A83.60 . This text examines the impact of various forms of technology on individuals as they age. It thoroughly explores both the opportunities and limitations of technology on various aspects of successful ageing. This is fundamentally an academic text, which nevertheless remains accessible and offers a wealth of valuable information on this important topic. As one contributor identifies, technology and ageing is an ‘en vogue’ topic. With the ageing of our populations, the promise of improved quality of life through technology is tantalizing indeed. As technology impacts further on our daily lives, the marginalisation of older people because of limited access is increasingly concerning. Clearly, this is an important area of research. This text, one of a series on the societal impact on ageing, thoroughly explores the available evidence on given topics, while posing new questions and outlining new findings. Its contributors are well-credentialed and each chapter is followed by commentaries from experts in the same and neighbouring disciplines. This approach ensures that each topic is examined from a number of perspectives and that points raised are thoroughly critiqued. The main topics include: design, useability and ageing; the impact of the Internet; everyday technology in the home; and assistive technology. The book's emphasis on the cultural context of technology and ageing, and on what it calls the ‘person–environment fit’, helps to ensure that everyday realities are foremost. Students and theorists in the field should find this book's thorough analysis of the given topics and comprehensive author and subject indexes very useful. It is structured and presented very clearly, with short, clearly-headed sections and good use of graphics. Despite its academic tone, this book remains readable and engaging. It therefore has much to offer to those of us seeking practical information that may promote older people's use of technology to access information, services and products. Service providers and practitioners, and even designers and marketers of technological products, can glean information about older people's technology-related needs. We learn, for example, that older people generally use technology more successfully when given appropriate hands-on training and when they understand the benefits that such technology can offer. We also learn that the use of a large font, contrasting background and backlighting of keys can compensate for age-related visual deficits. Examples of assistive technologies such as verbal prompting devices to aid people with cognitive impairment are given and analysed. Information on other print and web-based resources on technology and ageing is also given, although somewhat buried within the text. Australian readers will struggle with some of the book's American phrasing and terms. Content is generally limited to US, Canadian and European research and analysis. While broad consideration is given to cultural contexts, the impact of technology on specific minority cultures is not well covered, particularly issues of language differences. Given the speed at which technology has affected our lives in recent decades, it is both exciting and daunting to imagine what the future may hold as we all age. Books such as this can enhance our understanding and help to ensure that the benefits of technology are maximised and the problems minimised.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.203
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2006
Admission routes1
Has abstractyes

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