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Record W3133331950 · doi:10.34257/gjhssdvol21is1pg9

Some ‘Terrestrial’ and ‘Celestial’ Issues Encountered in Dowsing ‘Old World’ Historical Sites

2021· article· en· W3133331950 on OpenAlexaboutno aff
John F. Caddy

Bibliographic record

VenueGlobal Journal of Human-Social Science · 2021
Typearticle
Languageen
FieldPsychology
TopicParanormal Experiences and Beliefs
Canadian institutionsnot available
Fundersnot available
KeywordsSubconsciousParanormalPsychologyPerspective (graphical)HistoryEpistemologyAestheticsPsychoanalysisPhilosophyComputer science

Abstract

fetched live from OpenAlex

In the following text I’ve pulled together some observations on the effects of celestial and ground energies I have run into while dowsing in Italy. But this ‘Old World’ perspective comes from a Canadian who has been resident in Italy for almost 40 years. I discuss dowsing the influences of ground and sky energy, following a hypothesis often used by those sensitive to paranormal phenomena. That is that potentially, humans have access to much more information about their environment than is available to the conscious mind, and that dowsing without equipment is also an option. In fact, it is necessary to go outside the usual boundaries of dowsing to make some important points. For example, Figure 1 suggested by Long (1948), should be borne in mind as my guiding hypothesis: It is worth asking the subconscious mind ‘his/her’ opinion on events that are affecting the subjective or conscious mind. In my case, having spent the recent pandemic alone, and since I became a widower last year, I’ve come to appreciate the viewpoint of my subconscious. No doubt some would describe this as a mental aberration but I now have ‘conversations’ with my subconscious, whom I address as ‘Frederick’. His answers to my questions, when they come, often later, appear as spontaneous thoughts or in dreams, and have proven their worth in practice.

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.047
GPT teacher head0.391
Teacher spread0.343 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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