Bibliographic record
Abstract
Purpose The purpose of this paper is to describe information seeking and use (ISU) within the context of minimalist lifestyles and connect characteristics of living with less to theories of information poverty and resilience. Design/methodology/approach Naturalistic methods of inquiry describe minimalist lifestyles in a remote, rural context through semi-structured interviews with 24 adults. Environmental scanning and visual methods extended data collection retrospectively and longitudinally to span almost 118 years of community history. Qualitative thematic coding and analysis proceeded inductively and reflexively. Findings Living minimally in this environment results in adaptive strategies that compensate for lack of resources in general, and information resources specifically. Positive psycho-social attitudes such as optimism, creativity, curiosity, resourcefulness, and self-sufficiency continue to be important factors in developing resilience in information seeking practices. Research limitations/implications Information poverty is usually defined relatively, and often in relation to formal, macro-level environments. Focussing attention on informal, local level ISU reveals alternate varieties of knowledge, ways of knowing and characteristics that create information resilience in the face of sometimes profound deficits. Practical implications Highlights of positive aspects to ISU in this remote, rural context will be of interest to researchers and practitioners serving rural library systems. Originality/value This study provides an historical and contemporary glimpse into the ISU patterns of a previously unexamined population and context, those who live minimalist lifestyles in a remote and rural location.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".