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Record W4360802689 · doi:10.5281/zenodo.7768329

The Role of Paywalls in Online Information-Seeking Behavior: A Review of Literature

2023· review· en· W4360802689 on OpenAlexaffabout
Richmond B. Yeboah, Joan C. Bartlett

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typereview
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This poster presents the first phase of a study into the effect of paywalls on the online information-seeking behavior of Canadian midwives. Using a narrative review approach, theauthorshave reviewed and synthesized the literature onthe effect of paywalls on information-seeking behavior.Important questions were raised about institutions and associations paying for access on behalf of their members. In addition, suggestions are made on the gaps that need to be filled, such as(a) a need to examine how the different types of paywall configurationsaffect online information-seeking behavior; (b) a need for more interviews and surveys to better understand the phenomenon;and (c) a need to examine the rolepaywalls play in aspects of online information-seeking behaviorotherthan the number of visits, downloads and article view times.

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)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.012
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.131
GPT teacher head0.391
Teacher spread0.260 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2023
Admission routes2
Has abstractyes

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