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Record W2964930663

The SAGE handbook of visual research methods (2nd Edition)

2019· book· en· W2964930663 on OpenAlexaboutno aff
Luc Pauwels, Dawn Mannay

Bibliographic record

VenueSAGE Publications eBooks · 2019
Typebook
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsDisciplineVisual cultureSociologyMedia studiesJournalismSocial scienceVisual artsArtAnthropology
DOInot available

Abstract

fetched live from OpenAlex

In introducing the first edition of The Sage Handbook of Visual Research Methods, Eric Margolis and Luc Pauwels (2011: xxi) argued that ‘the future of visual research will depend on the continued effort to cross disciplinary boundaries and engage in constructive dialogue with different schools of thought’. This cross disciplinary pursuit is very much echoed in the second edition where we engage with the accounts of researchers working in different traditions, including anthropology, art and design, communication, cultural studies, education, film and media studies, geography, gender studies, history, literature, photography, journalism, psychology and sociology. Consequently, the volume brings together distinct scholarly traditions, providing an opportunity for reflection across disciplinary boundaries, and for shedding new light on common problems and opportunities stimulated by research in the field of visual studies. Scholars of disciplines and fields of enquiry not directly represented in this book, may nevertheless find inspiration, guidance and encouragement to take forward their interests in visual research methods. The volume introduces a range of contexts and sites. The authors themselves have been drawn from wide geographical spread, representing an international interest in the visual, and including the nations of Australia, Austria, Belgium, Brazil, Canada, Denmark, England, Germany, North America, Scotland, South Africa, Sweden, Switzerland, and Wales. The sites of interest are equally varied and the authors offer insights into the natural environment, historical archives, social media, food packaging, and therapeutic practice – to name but a few. In exposing readers to these different disciplinary practices and research contexts, we hope to encourage them to reflect on how this knowledge can inform their own visual fields of interest. The book welcomes back 25 of the original authors from the first edition, who have updated, and in some cases, completely re-written their foundational contributions. They are joined by 31 new contributors to the second edition, who offer fresh perspectives and extend the knowledge base by reflecting on their innovative work in visual studies and methodologies. Authors in the collection are both well-known names if the field of visual research, and scholars who are relatively new academic voices. In editing this collection, we have gained a wealth of knowledge, developed more nuanced understandings of visual research methods, and at the same time gained a deeper appreciation of different research approaches, perspectives and applications. As in its first edition, the handbook does not aim to present a consistent view or voice, but rather to exemplify diversity and contradictions in perspectives and techniques. It is noteworthy, then, that the authors in this collection have brought opportunities for the reader to reflect on, challenge and extend their own thinking on visual research methods, and complicate their understandings of epistemology, methodology, reflexivity and ontology. Crucially at the core of these chapters are theoretical and methodological debates about the meanings and study of the visual, presented in vibrant accounts of research design, analytical techniques, fieldwork encounters and data presentation.

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)0.043
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.816
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.606
GPT teacher head0.685
Teacher spread0.079 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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