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Record W2940222054 · doi:10.1002/asi.24222

The ubiquitous digital file: A review of file management research

2019· review· en· W2940222054 on OpenAlex

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

VenueJournal of the Association for Information Science and Technology · 2019
Typereview
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceUploadFocus (optics)File sharingWorld Wide WebData scienceThe Internet

Abstract

fetched live from OpenAlex

Computer users spend time every day interacting with digital files and folders, including downloading, moving, naming, navigating to, searching for, sharing, and deleting them. Such file management has been the focus of many studies across various fields, but has not been explicitly acknowledged nor made the focus of dedicated review. In this article we present the first dedicated review of this topic and its research, synthesizing more than 230 publications from various research domains to establish what is known and what remains to be investigated, particularly by examining the common motivations, methods, and findings evinced by the previously furcate body of work. We find three typical research motivations in the literature reviewed: understanding how and why users store, organize, retrieve, and share files and folders, understanding factors that determine their behavior, and attempting to improve the user experience through novel interfaces and information services. Relevant conceptual frameworks and approaches to designing and testing systems are described, and open research challenges and the significance for other research areas are discussed. We conclude that file management is a ubiquitous, challenging, and relatively unsupported activity that invites and has received attention from several disciplines and has broad importance for topics across information science.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.022
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.674
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0030.001
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 head0.289
GPT teacher head0.510
Teacher spread0.221 · 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