THE QUARTER-LIFE CRISIS EXPERIENCED BY MEGAN IN LYNN SHELTON’S LAGGIES
Bibliographic record
Abstract
Laggies (2014) is an independent movie directed by young director Lynn Shelton and writer Andrea Siegel. Laggies tells the story of Megan who experiences quarter-life crisis. Quarterlife crisis is a period of constant change, instability, and identity confusion. It hits young adult in the age of early 20s until early 30s where the adolescence transforms into the adulthood. In the movie Laggies, the main character, Megan suffers from quarter-life crisis in which she is in her mid-20s but she does not know what she wants to do for her future. In this thesis, the writer will describe the intrinsic aspects, which are narrative and cinematography elements and extrinsic aspect of the movie which is the quarter-life crisis experienced by the character. The objective of this study is to explain the quarter-life crisis experienced by the character in the movie Laggies. The method used in collecting the data is library research while the approach used is exponential approach to describe the intrinsic aspects and social psychological approach to describe the extrinsic aspects. The result of this thesis is that Megan in the movie Laggies has finally overcome her quarter-life crisis and lived according to her interest and values of life.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".