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First Things First: Exploring Maslow’s Hierarchy as a Service Prioritization Framework

2019· article· en· W2980094303 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

VenueWeave Journal of Library User Experience · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaslow's hierarchy of needsHierarchyPrioritizationService (business)Computer scienceProcess managementBusinessPsychologyPolitical scienceSocial psychologyMarketing

Abstract

fetched live from OpenAlex

This paper proposes a model for categorizing library services and resources by their importance to users based on the service’s fundamentality to the other resources and services in the library’s offerings, the degree to which the service affects users, and the scope of users that access the service. Adapted from Abraham Maslow’s theory of motivation, we substitute individual human motivations for a community’s motivations for using the library. Maslow’s five tiers—physiological needs, safety needs, love and belongingness needs, esteem needs, and self-actualization—are changed to library-specific tiers: Library as Minimum Viable Product, Library as Convenience, Library as Connector, Library as Incubator, and Community as Library. The Hierarchy of Library User Needs is a theoretical tool for service prioritization with the potential to facilitate discussions between users and libraries. Libraries may wish to (re)evaluate the alignment between the resources they devote to their services and the items that are most likely to be used and appreciated by their users.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.021
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.241
Teacher spread0.212 · 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