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The Methodology of Archival Science and Archival Method: the Discussion Continues

2018· article· en· W3097706132 on OpenAlexaboutno aff
Valentyna Bezdrabko

Bibliographic record

VenueArchivi Ukraїni · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsArchival scienceComputer scienceData scienceLibrary science

Abstract

fetched live from OpenAlex

An important theoretical issue of archival studies – methodology has been updated. Referring to the works of well-known foreign researchers Luciana Duranty and Giovanni Miketti, the theme of the universal method in science, interdisciplinary borrowing and methodological pluralism has been raised. Honesty and controversy of colleagues’ considerations led to more active development of foreign archival methodological experience. References: Bloch, M. (1967). The Historian’s Craft. Manchester: University Press. [in English]. Born, L. K. (1941). Baldassarre Bonifacio and His Essay “De Archivis”. The American Archivist, 4, 221–237. [in English]. https://doi.org/10.17723/aarc.4.4.36u35457n6g45825 Born, L. (1955). The “De Archivis commentarius” of Alberto Barisoni, 1587–1667. Archivalische Zeitschrift, 50/51, 12–22. [in English]. https://doi.org/10.7788/az-1955-jg03 Brenneke, А. (1953). Archivkunde, ein Beitrag zur Theorie und Geschichte des europäischen Archivwesens. Leipzig: Koeheler & Amelang. [in German]. Cassese, L. (1955). Del metodo storico in Archivistica. Società, 5, 878–885. [in Italian]. Cencetti, G. (1970). Scritti archivistici. Roma: Il Centro di ricerca editore. [in Italian]. Duranti, L. (2009). In M. Bates, M. N. Maack & M. Drake (Ed.), Encyclopedia of Library and Information Science. New York–Basel–Hong Kong: Marcel Dekker. [in English]. Duranti, L. (2000). Diplomatics: New Uses for an Old Science. In H. MacNeil, Trusting Records: Legal, Historical, and Diplomatic Perspectives (pp. 77–85). Dordrecht: Kluwer Academic Publishing Group. [in English]. Duranti, L. & Michetti, G. (2017). The Archival Method. In Research in the Archival Multiverse (pp. 75–96). Clayton: Monash University. [in English]. Gilliland, A. J., McKemmish S. & Lau A. J. (2017). In Research in the Archival Multiverse. Clayton: Monash University Publishing. [in English]. https://doi.org/10.26530/OAPEN_628143 Turner, Ja. (1990). Experimenting with New Tools: Special Diplomatics and the Study of Authority in the United Church of Canada. Archivaria, 30, 91–103. [in English]. Dekart, R. (1989). Rassuzhdenie o metode, chtoby verno napravliat svoy razum i otyskivat istinu v naukah [Reflections on method to direct own mind correctly and find truth in sciences]. In R. Dekart, Sochineniia (vol. 1, pp. 250–296). Moskva: Mysl. [in Russian]. Kuleshov, S. H. (2000). Dokumentoznavstvo: istoriia. Teoretychni osnovy [Document science: history. Theoretical basis]. Kyiv. [in Ukrainian]. Matiash, I. (2012). Arkhivoznavstvo: metodolohichni zasady ta istoriia rozvytku: navchalny posibnyk [Archival science: methodological basis and history of development: study guide]. Kyiv: Vydavnychy dim “Kyievo-Mohylianska akademiia”. [in Ukrainian].

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)0.099
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.099
Threshold uncertainty score0.526

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0990.077
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.015
Science and technology studies0.0110.084
Scholarly communication0.0270.035
Open science0.0050.010
Research integrity0.0140.020
Insufficient payload (model declined to judge)0.0070.002

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 head0.073
GPT teacher head0.298
Teacher spread0.225 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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".

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Citations1
Published2018
Admission routes1
Has abstractyes

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