Bibliographic record
Abstract
"Human beings have a fundamental connection to “home.” Christian leaders all have the underlying goal of leading the way home. We speak of heaven as home; we use phrases like, “home is where the heart is,” and “home Sweet home.” When circumstances are difficult, when we are worn and discouraged, we lean on life’s tired dreams and murmur, “i just want to go home.” home means many things to each of us, but i think that language is one of the vehicles that takes us home. For example, i always jump when i hear a Canadian accent, and i say “Hey, you speak Canadian!” it brings memories of my childhood leaping back, and never fails to make me smile. i was born and raised in Canada, and although i have been in the United States more years than i spent up north, in many ways Canada will always be home. this concept, imaged by the word “home,” shows that language possesses the characteristics of relativity and determinism, which can influence our thoughts and in turn affect a culture. this is why looking at language as leadership can show how, through the context of verbal phrases or proverbs, words like “home” can change our direction. What does this basic idea of language mean for Christian leadership? Could it be that understanding the deep pathos in this particular philosophical wordcontext (like the word “home”) might give leaders a tool by which they can truly achieve transformation? For example, do the words we use take others to a path that leads them home, whatever “home” may be to them? i believe language indeed can be used as leadership in this way."
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".