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Record W2150622787 · doi:10.18438/b8bs5p

Ethnographic Methods are Becoming More Popular in LIS Research

2013· article· en· W2150622787 on OpenAlex
Diana Wakimoto

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEvidence Based Library and Information Practice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographyLibrary scienceInclusion (mineral)SociologyComputer scienceSocial scienceAnthropology

Abstract

fetched live from OpenAlex

A Review of:
 Khoo, M., Rozaklis, L., & Hall, C. (2012). A survey of the use of ethnographic methods in the study of libraries and library users. Library & Information Science Research, 34(2), 82-91. doi: 10.1016/j.lisr.2011.07.010 
 
 Objective – To determine the number of ethnographic studies of libraries and library users, where these studies are published, how researchers define ethnography, and which methods are used by the researchers. 
 
 Design – Literature survey.
 
 Setting – The researchers are located at Drexel University, Philadelphia, Pennsylvania, United States of America. 
 
 Subjects – 81 ethnographic studies of libraries and library users.
 
 Methods – The researchers conducted a literature survey, starting with a pilot study of selected library and information science (LIS) journals, to find ethnographic studies and to determine key terms in research using ethnographic methods. The researchers used these terms in the main study to identify more LIS research using ethnographic methods. The same journals used in the pilot study were then searched online as part of the main study, along with three LIS databases (LISA, LISTA, LLIS). The researchers also searched the open web in order to capture grey literature in the LIS field. All literature found, including those sources found through secondary citations, was screened for inclusion in coding. Studies with non-LIS settings were excluded as were studies that utilized non-ethnographic methods. The screened studies were coded to determine categories of methods used. 
 
 Main Results – The researchers found 81 articles, reports, and conference presentations that used ethnographic methods, which they compiled into a bibliography. This is an order of magnitude larger than that found by previous literature surveys. Of these studies, 51.9% were published after 2005. The majority (64.2%) of the studies were published in journals. Many studies did not provide clear or detailed definitions of ethnography and the definitions that were provided varied widely. The researchers identified themes which had been used to support ethnographic methods as a research methodology. These included using ethnographic methods to gain richer insight into the subjects’ experiences, to collect authentic data on the subjects’ experiences, and to allow flexibility in the methods chosen. They also included the use of multiple data collection methods to enable data triangulation. The five main method categories found in the literature were: observation, interviews, fieldwork, focus groups, and cultural probes. 
 
 Conclusion – Based on the relatively large number of ethnographic studies identified when compared to previous literature surveys and on the upward trend of publication of ethnographic research over the past five years, the authors noted that their overview study (and resultant compilation of literature from disparate sources) was important and time-saving for researchers who use or are beginning to use ethnography as a research methodology.

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)0.014
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.783
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.215
Open science0.0000.000
Research integrity0.0000.001
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 head0.188
GPT teacher head0.512
Teacher spread0.324 · 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