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Record W2025285469 · doi:10.58680/rte202231642

Annotated Bibliography of Research in the Teaching of English

2022· article· en· W2025285469 on OpenAlex
Lisa Ortmann, Anne Crampton, Erin Stutelberg, Richard Beach, Keitha-Gail Martin-Kerr, Debra Peterson, Anna Schick, Bridget Kelley, Charles R. Lambert, Tracey Pyscher, LeAnne Robinson, Mikel W. Cole, Kathryn Allen, Candance Doerr-Steven, Madeleine Israelson, Robin Jocius, Tracey Murphy, Stephanie Rollag Yoon, Andrea Gambino, Jeff Share, Stephanie M. Madison, Katherine Brodeur, Amy Frederick, Anne Ittner, Megan McDonald Van Deventer, Ian O’Byrne, Sara K. Sterner, Mark Sulzer

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.

Bibliographic record

VenueResearch in the Teaching of English · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAnnotated bibliographyBibliographyEducational researchMathematics educationPsychologyLinguisticsPedagogySociologyLibrary scienceComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Since 2003, RTE has published the annual “Annotated Bibliography of Research in the Teaching of English,” a list of curated and annotated works reviewed and selected by a large group of dedicated educator-scholars in our field. The goal of the annual bibliography is to offer a synthesis of the research published in the area of English language arts within the past year for RTE readers’ consideration. Abstracted citations and those featured in the “Other Related Research” sections were published, either in print or online, between June 2020 and June 2021. The bibliography is divided into nine sections, with some changes to the categories this year in response to the ever-evolving nature of research in the field. Small teams of scholars with diverse research interests and background experiences in preK–16 educational settings reviewed and selected the manuscripts for each section using library databases and leading scholarly journals. Each team abstracted significant contributions to the body of peer-reviewed studies that addressed the current research questions and concerns in their topic area.

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)0.074
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0740.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0130.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.009
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 head0.137
GPT teacher head0.391
Teacher spread0.254 · 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