Bibliographic record
Abstract
The rock-art of Point Pleasant Park has been largely unacknowledged by academic research and popular narratives. This study seeks to remedy such oversight by exploring the function of this contemporary assemblage, based on the (1) frequency, (2) placement, and (3) content of the art. To productively encompass and limit the research focus, this study defines rock-art as human-made images, designs, or writing, irrespective of stylistic qualities, which occur on natural rock faces but not human-built features. Phase One data collection located rock-art throughout the 190-acre park via unstructured field-walking. Figure locations were mapped on paper, using visual estimation and cellphone GPS. Five areas of intense activity were identified. The current estimate for rock-art within the park is 488 figures, consisting of 375 petroglyphs and 113 pictograms. The coastal region near Chain Rock was selected for Phase Two, in-depth cataloguing and analysis. The majority of the target site figures are names, effectively and sometimes explicitly, stating "I was here". Culture is embedded in other works, such as Pacman ghosts or a quote from Dr. Seuss' The Lorax. \nLiteracy has caused Haligonian rock-art to diverge from pictures as the \npredominate means of artistic rock adornment and communication of ideas; they instead rely on text. Yet these modern humans are still engaged in a vernacular form of meaning making. Many researchers posit that rock-art is a human universal, suggesting that literate humans have continued this practice, albeit in modified form. Rock-art, varied as it is in appearance, time, place, and purpose, functions less as an artifact, or a collection of \nartifact-types; it more closely functions as a conversation.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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.
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".