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Record W4380231404 · doi:10.1515/9780228018131

Generation Why

2023· book· en· W4380231404 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2023
Typebook
Languageen
FieldSocial Sciences
TopicGenerational Differences and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Perhaps more than ever before, young people entering the workforce are searching for meaning and authenticity in their careers. This book helps managers understand the postmodern worldview held by generation Z and younger millennials, how it influences their behaviour at work, and how they want to be led in the workplace. Karl Moore takes a practical and down-to-earth approach to understanding what drives millennials and generation Z and how the education system they were brought up in has informed their worldview. Based on hundreds of interviews conducted with under-thirty-year-olds across Canada, the United States, Japan, Iceland, the United Kingdom, and elsewhere, as well as interviews with executives to gain their perspectives on changing dynamics in the workplace, Generation Why provides a thorough study of these generations’ ideas about truth, hierarchy, and leadership. Focusing on listening, purpose, reverse mentoring, feedback, and how people relate to each other in the workplace, Generation Why provides the essential tools for effectively working with millennials and generation Z and unlocking their full professional potential.

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.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.797
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.053
GPT teacher head0.258
Teacher spread0.205 · 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