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Record W4309613421 · doi:10.21435/tl.274

Kulttuurien tutkimuksen menetelmät

2022· book· en· W4309613421 on OpenAlexfundno aff
Konsta Kajander, Tiina-Riitta Lappi

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsnot available
FundersTerveyden ja hyvinvoinnin laitosUniversity of TorontoSuomalaisen Kirjallisuuden SeuraNational Library of AustraliaUniversity of OxfordUniversity of Chicago
KeywordsReflexivityEthnographySociologyHumanismCultural analysisEpistemologySocial scienceAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

This collection deals with cultural studies in the humanities and the methods it uses. Its authors include scholars of ethnology, anthropology, folkloristics, digital culture research, and study of religions. Its chapters address topics of discussion and debate in humanistic culture research and indicate what tools are currently being used to study cultural phenomena. Various phases of the research process are covered, including epistemology, research ethics, techniques of data collection and analysis, the writing process of research plans, and the process of writing up the analysis. The book’s authors contribute to our knowledge of changes in research paradigms and agendas, scientific philosophies, ethnographic fieldwork, different modes of writing, materiality, reflexivity, observation, researchers’ use of the five senses, digital research, audiovisual techniques of observation, and selected textual methodologies. The book is intended as a textbook and methods guide for students in the fields of cultural research, for postdoctoral researchers, and for more senior researchers.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.089
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0890.047

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 head0.078
GPT teacher head0.427
Teacher spread0.349 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations6
Published2022
Admission routes1
Has abstractyes

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Same topicResearch in Social SciencesFrench-language works237,207