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Record W2493683798 · doi:10.1057/9780230245396_4

Geeks Who Care: Gender, Caring and Community Access Computers

2009· book-chapter· en· W2493683798 on OpenAlexaffabout
Leslie Bella

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2009
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMasculinityNeighbourhood (mathematics)Health careWork (physics)SociologyGender studiesPublic relationsPsychologyPolitical science

Abstract

fetched live from OpenAlex

Caring work, both professional and informal, supports the social networks that are key determinants of health. Caring theory reveals this work as gendered. Direct caring work, generally understood as women’s work, has been devalued and even rendered invisible. Men have been more involved in more visible executive caring. While direct caring is likely to be women’s work, technology has generally been associated with men and masculinity. This chapter shows how these two contrasting gendered processes of care and technology interweave at a particular community-based setting. The MacMorran Community Centre is located in a low-income neighbourhood of St John’s, Newfoundland,1 and offers programmes to enhance the health and well-being of residents, including a programme of public access computers. Interviews with 25 key informants allowed us to explore the intersection of gendered processes involving technology on the one hand and caring on the other. We focus on ‘executive care’ (a more stereotypically masculine activity), ‘direct care’ (more stereotypically feminine) and receiving care, and on perspectives on the technology that may be intrinsic (more stereotypically masculine perspective) or instrumental (more stereotypically female). Our analysis reveals more involvement of men in caring (both executive caring and more visible, direct care), a development that appeared to enhance the community’s abilities to support the health of its members.

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), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.060
GPT teacher head0.303
Teacher spread0.243 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations0
Published2009
Admission routes2
Has abstractyes

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