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Record W4403433625 · doi:10.1002/pra2.1004

With a Little Help from Our Friends: Applying a Critical Friends Orientation to Critical Literature Reviews

2024· article· en· W4403433625 on OpenAlexaff
Danielle Allard, Tami Oliphant

Bibliographic record

VenueProceedings of the Association for Information Science and Technology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOrientation (vector space)PsychologySociology

Abstract

fetched live from OpenAlex

ABSTRACT This paper describes how we developed and applied an exploratory critical friends orientation to a critical literature review that explores how feminist theories and approaches have been used in archival studies literature and reports on insights generated by this method. A critical friend is a trusted ally and critic who both values our ideas and can push them forward. Our “critical friends” critical literature review includes two parts; using traditional critical review methods we identify and synthesize how critical feminist approaches have been employed in archival studies literature. Atypically, and in part two, we also pay attention to those scholarly articles that discussed relevant or related concepts but were ultimately excluded from our final literature review corpus during the appraisal process. These peripheral articles act as critical friends to the research area under review. We describe how this approach identifies disciplinary boundaries and traditions and explores areas of overlap across intersecting and adjacent fields. A critical friends approach allows us to generously interpret and analyze the complex concepts of “feminisms” and “archives” across disciplinary fields in order to identify, learn from, and engage across fields that have much in common as well as fundamental differences.

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)0.003
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.006
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 head0.017
GPT teacher head0.386
Teacher spread0.369 · 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.

Study designTheoretical or conceptual
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

Citations3
Published2024
Admission routes1
Has abstractyes

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