Bibliographic record
Abstract
The ever-increasing speed and reach of Information and Communication Technologies (ICTs) are often lauded for the beneficial social effects we are told they have. This raises questions about the connection between knowledge and social relationships, especially concerning meaningful relationships in a world where people are increasingly represented as data. To answer this question, one approach is to consider the role of documents in communicating “meaningful” content in pursuit of understanding. Because this is difficult to articulate, this paper takes the approach of using metaphors—specifically of the document as a bridge, a window, a painting, a briefcase, and a mirror—to consider the possibilities for documents to aid or impede relationships. To provide something concrete upon which to reflect, this paper applies the metaphors to documents that are explicitly tied to meaning about individuals: those created by the United Church of Canada as part of its process of reconciliation with Canada’s Indigenous people. Thinking about the church’s documents through the lens of metaphors is an initial conceptual step in thinking about the meaning in these documents. Through the metaphors, we gain important insights into the extent to which documents connect individuals as they are called to in the ICT environment.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.033 |
| Scholarly communication | 0.009 | 0.019 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
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".