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She reads, he reads: gender differences and learning through self-help books

2015· article· en· W2166753535 on OpenAlex
Brandi Kapell, Scott McLean

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEuropean Journal for Research on the Education and Learning of Adults · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsReading (process)Volition (linguistics)PsychologyAction (physics)PoliticsInterpersonal communicationSocial psychologyDevelopmental psychologyGender studiesSociologyPolitical science

Abstract

fetched live from OpenAlex

Despite considerable scholarly attention given to self-help literature, there has been a lack of research about the experience of self-help reading. In this article, we explore gender differences in self-help reading. We argue that men and women read self-help books for different reasons and with different levels of engagement, and that they experience different outcomes from reading. We provide evidence from in-depth interviews with 89 women and 45 men. Women are more likely to seek out books of their own volition, to engage in learning strategies beyond reading, and to take action as a result of reading. Men are more likely to read books relating to careers, while women are more likely to read books about interpersonal relationships. We argue that these gender differences reflect profound political-economic and cultural changes, and that such changes also help explain the gendered evolution of adult, continuing, and higher education in recent decades.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
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 integrity0.0000.001
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 head0.206
GPT teacher head0.361
Teacher spread0.154 · 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