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Record W2232396140

Prolonging working lives in information technology employment

2006· other· en· W2232396140 on OpenAlexaboutno aff
Libby Brooke

Bibliographic record

VenueSwinburne Research Bank (Swinburne University of Technology) · 2006
Typeother
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessLabour economicsInformation technologyPublic relationsEconomicsPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

The research was undertaken within the Workforce Ageing in the New Economy project funded by the Canadian Social Sciences and Humanities Research Council, involving Canada, Australia, United States and three EU countries. The paper is concerned with the issue of whether working in rapidly changing IT employment is leading to de-standardization of the life course and prolonging of working lives beyond 65. The main aims of the paper were to examine whether new versions of extended careers are emerging in IT employment, how age relations between younger and older workers affect IT careers and whether and how the life course of IT workers is being refashioned through their careers in IT. The findings are based on analyses of focused interviews with around seventy information technology workers in eight small to medium companies. The research examined whether working in IT employment is changing the expectations of standard life course of retiring at 65. Exploration of relations between the ages indicated that age relations tended to support existing retirement expectations rather than retention. Despite the potentiality for change and for reconstructing careers, perspectives of truncated careers persisted rather than of careers as lengthening. Nevertheless new sequences of careers were found which varied according to type of IT work and positions. Factors in retention included opportunities for training and some innovative human resources options. The analysis indicates that ageist expectations of working lives persist and that new human resources policies have yet to be tailored to prolonging working lives within new economy IT employment.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.549
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.005
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.108
GPT teacher head0.379
Teacher spread0.271 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2006
Admission routes1
Has abstractyes

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