HUBUNGAN ANTARA ADAPTABILITAS KARIR DAN SUBJECTIVE WELL-BEING PADA LULUSAN BARU UNIVERSITAS AIRLANGGA
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui hubungan antara adaptabilitas karir dan subjective well-being (SWB), antara adapabilitas karir dan dimensi-dimensi SWB, antara SWB dan dimensi-dimensi adaptabilitas karir, serta antara dimensi-dimensi adaptabilitas karir dan SWB pada lulusan baru Universitas Airlangga. Adaptabilitas karir adalah konstruk psikososial yang menunjukkan sumber kebutuhan seseorang agar berhasil mengelola dan mengantisipasi transisi karir yang berlaku saat ini (Savickas 1997). SWB adalah evaluasi seseorang atas kehidupannya yang meliputi penilaian kognitif atas kepuasan dan penilaian afektif dari mood dan emosi (Kesebir & Diener, 2008 dalam Satyo, 2012). \nMetode yang digunakan adalah survey menggunakan kuisioner psikologis, dimana variabel adaptabilitas karir diukur menggunakan Career Adapt-Ability Scale (CAAS) dan variabel subjective well-being diukur menggunakan Memorial University of Newfoundland Scale of Happiness (MUNSH). Kedua variabel tersebut diujikan pada 168 lulusan baru Universitas Airlangga yang lulus pada tahun 2015 atau 2016. Metode pengambilan sampel dilakukan menggunakan metode accidental sampling dengan memberikan kuisioner secara online \nHasil penelitian ditemukan bahwa terdapat hubungan yang signifikan pada adaptabilitas karir dengan SWB (sig = 0,00 r = 0,29), SWB dengan semua dimensi adaptabilitas karir (perhatian sig = 0,02 r = 0,18; pengendalian sig = 0,00 r = 0,33; keingintahuan sig = 0,01 r = 0,21; kepercayaan diri sig = 0,00 r = 0,23), dimensi kontrol dengan semua dimensi SWB (PA sig = 0,00 r = 0,38, NA sig = 0,01 r = -0,21, PE sig = 0,00 r = 0,30, NE sig = 0,00 r = -0,26)
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".