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Record W2115473094 · doi:10.1109/hicss.1997.663366

Fragmented lives: how do teleworking parents juggle work and children care?

2002· article· en· W2115473094 on OpenAlexafffund
David F. Hardwick, Janet W. Salaff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaInformation Technology Research CentreUniversity of Toronto
KeywordsWork (physics)Control (management)Affect (linguistics)TelecommutingChild careSpace (punctuation)Unitary stateCare workPsychologySociologyBusinessPublic relationsManagementNursingEngineeringComputer sciencePolitical scienceMedicineCommunicationEconomics

Abstract

fetched live from OpenAlex

Teleworking, when full time employees give up dedicated space in a central office and work from home using telecommunications technologies, is a new form of work. Many researchers and practitioners hope that teleworkers can enjoy a more unitary and less fragmented life style. To learn how parents juggle their paid work and child care when they work at home, this paper draws on material from a subgroup of 21 teleworkers with children under age 12. They work for the same large telecommunications firm. We find that teleworking is not a unitary pattern of work, and the ways people do their work greatly affects how they take care of their children. The structure of their job, their interdependence and communication with co-workers and clients affect the control over the time and place of paid work. Those employees with more control over their immediate work conditions can do a wider range of child work than can those whose work is controlled by others in their work network. In sum, control over the time and place of paid work determines the ways they do their child care work.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.255
Teacher spread0.233 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations3
Published2002
Admission routes2
Has abstractyes

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