MCLACHLAN, SARAH (28 JAN 1968–)
Bibliographic record
Abstract
Best known as the founder of Lilith Fair, a tour providing a forum for female artists, Sarah McLachlan emerged from the 1990s as one of the highly regarded-and commercially successful-singer/songwriters on the music scene. Both her recordings and Lilith Fair have encouraged countless women to consider popular music as a viable career option. Born in Halifax, Nova Scotia, McLachlan took piano, guitar, and voice lessons as a youth. Attracting the interest of the Nettwerk label while performing with the new wave act, October Game, she recorded Touch (Nettwerk 30024; 1988; released in the U.S. by Arista #18594; 1989; #132), which went gold in Canada. The follow-up, Solace (Arista #18631; 1991; #167), showed McLachlan to be treading water. However, the next LP, Fumbling Towards Ecstasy (Arista #18725; 1993; #50), with its insightful song lyrics-most notably, adding a sociopolitical dimension to her prior concentration on personal relationships-complementing her expressive singing, represented an artistic breakthrough. The momentum generated by its triple platinum sales extended to the next album of newly recorded material, Surfacing (Arista #18970; 1997; #2), which ultimately sold more than 7 million copies on the strength of three hit singles: “Adia” (Arista #13497; 1998; #3), “Angel” (Arista #13497/13621; 1997; #4), and “Building a Mystery” (Arista #13395; 1997; #13). The LP also won Grammy awards for Best Female Pop Vocal and Best Pop Instrumental Performance.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.322 | 0.005 |
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; both teacher heads agree on what is shown here.
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".