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Record W2205412731 · doi:10.5539/gjhs.v8n9p26

Investigating Information-Seeking Behavior of Faculty Members Based on Wilson’s Model: Case Study of PNU University, Mazandaran, Iran

2015· article· en· W2205412731 on OpenAlex
Fereydoon Azadeh, Shahrzad Ghasemi

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

VenueGlobal Journal of Health Science · 2015
Typearticle
Languageen
FieldComputer Science
TopicInformation Retrieval and Search Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

The present research aims to study information seeking behavior of faculty Members of Payame Noor University (PNU) in Mazandaran province of Iran by using Wilson's model of information seeking behavior. This is a survey study. Participants were 97 of PNU faculty Members in Mazandaran province. An information-seeking behavior inventory was employed to gather information and research data, which had 24 items based on 5-point likert scale. Collected data were analyzed in SPSS software. Results showed that the most important goal of faculty members was publishing a scientific paper, and their least important goal was updating technical information. Also we found that they mostly use internet-based resources to meet their information needs. Accordingly, 57.7% of them find information resources via online search engines (e.g. Google, Yahoo). Also we concluded that there was a significant relationship between English language proficiency, academic rank, and work experience of them and their information- seeking behavior.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
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 head0.104
GPT teacher head0.365
Teacher spread0.261 · 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