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Record W2765289589

The Challenges, Tensions and Possibilities of Homeschooling: An Autoethnography of One Educator’s Homeschooled Journey

2017· article· en· W2765289589 on OpenAlexaboutno aff
Kathleen Ann Virban

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsAutoethnographySociologyPedagogyAestheticsGender studiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

The traditional method of acquiring and receiving an education in Canada is to send children to government run schools, funded by the public. The promise of education attained through traditional schooling remains on structured and formal learning. Concerned about the education and safety of their children, an increasing number of parents are seeking educational alternatives. My family, in particular, sought out a new reform: the promise of homeschooling. This thesis adopted a qualitative approach using autoethnography to examine my perceptions and my realities on the subject of homeschooling, while interrogating the promise of education along intellectual, social, and interpersonal dimensions. This qualitative inquiry is designed to discover more deeply the feelings and perceptions that emerge when homeschooling occurs while an essentialism educational philosophy and an authoritarian teaching style is dominant in the classroom. I will share my personal experience engaging in cultural, educational, and social pressures and will provide insights on these approaches from a homeschooled student’s perspective as a researcher.

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)0.010
metaresearch head score (Gemma)0.016
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 score0.014
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0140.019
Scholarly communication0.0060.005
Open science0.0020.006
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0020.001

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 head0.098
GPT teacher head0.321
Teacher spread0.223 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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