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Record W7017800758

British Girls’ and Women’s Magazines at the University ofWaterloo

2020· article· en· W7017800758 on OpenAlexaboutno aff

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
Fundersnot available
KeywordsTRIPS architectureMicroformPlan (archaeology)Work (physics)New englandBalance (ability)Club
DOInot available

Abstract

fetched live from OpenAlex

I am a European historian, specializing in British girls’ magazines, but I do my research in Canada. How can this be? Like many, my path in academia has not been a straight one. I completed the bulk of my BA with one daughter; my second daughter was born the summer before I began my fourth year. It was around the same time that I decided to change my original plan of becoming a high school social studies teacher, opting instead for graduate school. Entering my MA with two children – one six, the other one – I had to carefully balance studying, researching, working as a TA, and family. I was grateful to stumble upon a microfilm collection of the first two years of The Girls’ Best Friend, a British girls’ publication, at the University of BC, facilitating my first foray into girls’ magazines and permitting me to more easily balance the various parts of my life. Entering the PhD program at Simon Fraser University, however, I thought that I would need to travel to England to continue my work on girls’ magazines. I was concerned: how would I fund this travel? How would I secure sufficient time to do my research? What about my family? For personal reasons, packing everyone up and relocating to England to allow sufficient\ntime to go through my sources was simply not possible; going alone would mean frequent, short trips to minimize the impact of my time away. Each of these options, though, resulted in a significant amount of stress.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.678

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 science0.0010.001
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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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