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Record W4409166189 · doi:10.1177/09593535251327891

#GentleParenting: Critiquing the “fifth shift” of intensive mothering in the “pandemic afterlives”

2025· article· en· W4409166189 on OpenAlexafffund
Evangeline Holtz‐Schramek

Bibliographic record

VenueFeminism & Psychology · 2025
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPandemicPsychologySociologyCoronavirus disease 2019 (COVID-19)Medicine

Abstract

fetched live from OpenAlex

#GentleParenting presents a novel trend in networked parenting communities. Its rise correlates with the COVID-19 pandemic, during which parents' access to medical professionals decreased significantly. In this vacuum, a group of lay parenting experts arose and continues to gain influence. Through a mixed-method study that combines critical discourse analysis and contextual visual discourse analysis, this article analyzes a dataset and sample of posts compiled from TikTok and Instagram. My findings suggest that an epochal shift in parenting culture is taking place, involving a break with some of the fundamental tenets of the previously dominant parenting trend of intensive mothering. Informed by feminist critiques, my analysis of #GentleParenting explicates a concept I call the "fifth shift" to describe the additional burdens involved in online parenting. While #GentleParenting can be understood as positive in its efforts to allow parents to regain control over childrearing, it also poses some challenges, including its propagation of wealthy, White feminist presentations in digital networks, as well as its insistence on adding additional parenting labor. While empathy is resonant in #GentleParenting via satire, questions remain regarding the political effects of this community.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.296

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.400
Teacher spread0.362 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2025
Admission routes2
Has abstractyes

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