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Record W4405765357 · doi:10.29173/iq1149

Evaluating new technologies and organizational structures

2024· article· en· W4405765357 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueIASSIST Quarterly · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicBusiness and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessComputer science

Abstract

fetched live from OpenAlex

Welcome to the last issue of IASSIST Quarterly for 2024, IQ 48(4). We are excited to share news of several developments that we have been working on over the last few months: The IASSIST Qualitative Social Science and Humanities Data Interest Group (QSSHDIG) is planning an IASSIST Quarterly special issue dedicated to the complexities of sharing qualitative data. For this special issue, we invite submissions of abstract proposals focused on the ethical challenges, methodological concerns, and labor involved in making qualitative data and research materials publicly available. The full CfP and details on how to submit an abstract can be viewed on the IASSIST Quarterly website: https://iassistquarterly.com/index.php/iassist/announcement/view/7 . The deadline for proposing articles is January 31st (full articles won’t be needed until later). We are delighted to welcome Minglu Wang as a new IQ Editorial Board member (as of October 2024). Minglu is the Research Data Management Librarian in the Open Scholarship Department at York University Libraries, York, Ontario, Canada. Among other qualifications, she brings experience as a member of the Editorial Board for ACRL’s College & Research Libraries (C&RL) (2019–2025), and she led the project group for that Board to investigate a data policy for C&RL. A new feature recently enabled on the OJS platform allows reviewers to link their profile with their ORCID iD. We mentioned last time that this will enable auto-loading of your articles to your ORCID profile, but the other effect is that it provides an opportunity for reviewers to receive credit and be acknowledged for their professional contributions. Note that the credit will merely note that you have served as a reviewer for the IQ—it will not indicate which article(s) you reviewed. Unfortunately, the IQ editorial team had to retract a paper from publication this fall due to plagiarism. The paper titled “Data protection and right to privacy legislation in Kenya” by Mankone, A. M. (2023), was published in IQ, 47(3-4). The full retraction notice can be found here. This new issue of IQ 48(4) presents four excellent papers. The first two evaluate methods to enhance findability of data deposited in data repositories. The subsequent two papers focus on organizational structure and improving organizational workflows. Kokila Jamwal in ”Boosting data findability: The role of AI-enhanced keyword” examines the use of Artificial Intelligece (AI) to supplement keywords that may be missing or inaccurately defined as a method to improve metadata and boost data findability. The author suggests that using this relatively new technology may reduce the time and effort required by data repositories staff for data curation and may enhance data findability and usability. Co-authors Knut Wenig and Xiaoyao Han are examining the findability of data deposited in data repositories that are using DDI metadata standards. Their paper ”State of DDI Cloud” invetigates the availability and the comprehensive element usage of DDI standards across 29 repositories registered on re3data.org. Based on their findings they provide recommendations for various stakeholders including the repositories, Dataverse developers, re3data.org, and the DDI Alliance. The article ”The IPUMS Business Process Model: Instituting a workflow mapping strategy to support archival processes” introduces the IPUMS workflow from external submission of data, harmonization process, documentation, extraction systems, and archival preservation of metadata. Author Diana Magnuson explains the value of instituting this mapping approach, and demonstrates the power of a clear business process model for developing archival goals in an organizational setting in which the archive function is vital but secondary to the main product. In ”Understanding motivations and future needs for data depoists at Korea Social Sciences Data Archive”, authors Hyowon Kim, Do Won Kim and Jungwon Yang evaluate the current data deposit process of the Korea Social Science Data Archive (KOSSDA). The data archive recently transitioned into an idependent researh center under Seoul National Univerity. Using interviews with stakeholders, they identify future needs and suggest a long-term strategy to ensure that the archive meets the needs of the academic community it supports. Wishing you a happy holidays season, and peace, health, and happiness in the New Year. Ofira Schwartz and Michele Hayslett, December 2024

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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