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Record W7162712620

Invest. You? Yes!

2017· other· en· W7162712620 on OpenAlexaboutno aff
Susan Long, Craig Johnson, Stephen M. Salisbury, Kristofer Kerchner, Ryan Murray, Oleg Gamzalev, Victoria Correll

Bibliographic record

VenueIndiana Magazine of History (Indiana University) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBaby boomersGeneration xQuarter (Canadian coin)CensusPopulationFertility
DOInot available

Abstract

fetched live from OpenAlex

The Millennials, also known as Generation Y, are the group of people who were born between the early 1980s and the early 2000s. Swelled by a resurgent fertility rate amongst Baby Boomers and Generation X, Millennials number 83.1 million and represent more than one quarter of the nation's population (U.S. Census Bureau, 2015). They are regarded as the "next great generation" (Howe and Strauss, 2000, p. 3). According to the National Chamber Foundation (2012), Millennials are the most racially and ethnically diverse generation, with 47% of Millennials classified as a minority (DeVaney, 2015). Being characterized in a number of different ways regarding their lifestyle preferences, career perspectives, and expectations, they are likely the most studied generation to date.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Other
Teacher disagreement score0.530
Threshold uncertainty score0.670

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.5300.413

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 head0.021
GPT teacher head0.200
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), 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
Published2017
Admission routes1
Has abstractyes

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