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Work, Family, and Identity

2021· book-chapter· en· W3137222905 on OpenAlexaff
Phil Lord

Bibliographic record

VenueAdvances in human resources management and organizational development book series · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsMcGill University
Fundersnot available
KeywordsWork (physics)Identity (music)Transition (genetics)SPARK (programming language)Political sciencePublic relationsSociologySocial psychologyPsychologyEngineeringComputer scienceAestheticsMechanical engineering

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has accelerated the existing transition to remote work and, more broadly, flexible forms of work. Much energy and attention have been dedicated to analysing this transition and how governments and other actors can best respond to it. This chapter takes a step back and analyses the potential impacts of the transition to remote work on our individual and collective identities. Recognising that work is an important part of who we are and has historically been a microcosm and a catalyst of broader social change, this chapter analyses how remote work challenges gender roles, contemporary family structures, and our conceptualisation of the relationship between work and other commitments. The chapter admittedly offers more questions than it does answers. It complexifies our understanding of remote work and seeks to spark future discussions as to its consequences.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.014
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.014
GPT teacher head0.253
Teacher spread0.239 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2021
Admission routes1
Has abstractyes

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