MétaCan
Menu
Back to cohort
Record W2554460942 · doi:10.1057/978-1-137-46781-2_28

Career Management Over the Life-Span

2016· book-chapter· en· W2554460942 on OpenAlexaboutno aff
Ulrike Fasbender, Jürgen Deller

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsPensionRetirement ageLife expectancyPopulation ageingDeveloped countryStatutory lawGermanDemographic economicsPopulationPolitical scienceEconomic growthEconomicsGeographyDemographySociologyFinance

Abstract

fetched live from OpenAlex

Career management over the lifespan has become increasingly important due to the extension of working lives in most developed and many developing countries. The extension of working lives, in fact, is a politically enforced phenomenon as a reaction of more or less constantly low birth rates and increased life expectancies that have caused global population ageing. In the last decade, several developed countries have introduced new regulations to gradually increase retirement age (i.e., eligibility age of receiving a public pension) from 65 to 67 in the mid-term future (e.g., Australia, Canada, Denmark, France, Germany, Greece, Israel, Netherlands, Poland, Spain, or the USA) (Organization for Economic Cooperation and Development [OECD] 2013). Further, plans to increase the retirement age even beyond 67 exist in some countries, such as in the UK, which plans an increase of retirement age to 68 between 2044 and 2046 (OECD 2013). In addition to the normal retirement age, some countries have implemented a policy to allow people, who have contributed for a certain time (e.g., 40 years in Greece or 45 years of minimum contributory record in Germany), to receive a public pension before retirement age (e.g., starting from 62 in Greece or 63 in Germany) (OECD 2013; German Statutory Pension Insurance Scheme 2015). These new regulations will have a critical impact on the labour market in the future.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.131
GPT teacher head0.342
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations13
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePalgrave Macmillan UK eBooksSame topicRetirement, Disability, and EmploymentFrench-language works237,207