Movielogr

movie poster

Rating: 9 stars

Tags

Netflix

Seen 1 time

Seen on: 05/22/2012

View on: IMDb | TMDb

The Big Heat (1953)

Directed by Fritz Lang

Crime | Drama | Film Noir

Most recently watched by sensoria

Overview

Tough cop Dave Bannion takes on a politically powerful crime syndicate.  Preserved by the Academy Film Archive in partnership with Sony Pictures Entertainment in 1997.

Rated NR | Length 89 minutes

Actors

Adam Williams | Glenn Ford | Jeanette Nolan | John Crawford | Celia Lovsky | Edith Evanson | Lee Marvin | Carolyn Jones | Robert Burton | John Merton | John Doucette | Harry Lauter | Howard Wendell | Dorothy Green | Gloria Grahame | Fritz Ford | Willis Bouchey | Michael Granger | Joseph Mell | Dan Seymour | Charles Cane | Peter Whitney | Linda Bennett | Jocelyn Brando | Alexander Scourby | Phil Arnold | Sidney Clute | Michael Ross | Douglas Evans | William Murphy | Paul Maxey | Lyle Latell | John Close | Ric Roman | Donald Kerr | Ted Stanhope | Byron Kane | Chris Alcaide | Laura Mason | Herbert Lytton | Phil Chambers | Al Eben | Mike Mahoney | Patrick Miller | William Vedder | Norma Randall | Ezelle Poule | Michael Jeffers | Robert Stevenson

Viewing Notes

Now that I’ve finally watched The Big Heat, it’s hard to imagine I’ve gone so long without seeing it. While technically a film noir, The Big Heat easily transcends the genre with uniquely strong female leads and a strong, moral leading man in Glenn Ford.

Lang does bring German expressionism to bear here, certainly, and it’s evident in the stark use of shadows and light throughout the movie. However, there’s a lot more at work here, including some bold statements on current, at the time, social issues, such as assertive post-war modern women. While they’re still portrayed in their classical wife and plaything roles—cooking, cleaning, taking care of the children, or as a sexual plaything—they also make their own decisions, to momentous effect here.

A young Lee Marvin plays a snarling lowlife, the exact opposite of Ford’s morally incorruptible cop, to great effect. He’s a lot of fun to watch and it’s a credit to his acting that you actively hate his character so much.

The real scene stealer is the talented and beautiful Gloria Grahame, who plays Marvin’s companion, for lack of a better word.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0013
Controller Execution Time ( Members / Movie Detail )  0.1817
Total Execution Time  0.1830
  GET DATA  
No GET data exists
  MEMORY USAGE  
541,408 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sensoria/movie_detail/7536
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.1581 seconds)  (Hide)
0.0003  
SELECT 1
FROM `ml_sessions`
WHERE `id` = '6ba3d704d5db15cf0525c7a3124a85da25c0f806'
AND `ip_address` = '216.73.216.6' ?>
0.1512  
SELECT GET_LOCK('5a48eae28d99dbbadaaf4334531ff95a', 300) AS ci_session_lock ?>
0.0004  
SELECT `data`
FROM `ml_sessions`
WHERE `id` = '6ba3d704d5db15cf0525c7a3124a85da25c0f806'
AND `ip_address` = '216.73.216.6' ?>
0.0004  
SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'sensoria'
 LIMIT 1 ?>
0.0004  
SELECT `MV`.`title_id`, `MT`.`tmdb_id`
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movies` `MV` ON `MV`.`title_id` = `MT`.`title_id`
WHERE `MV`.`movie_id` = 7536
AND `MV`.`user_id` = 1
 LIMIT 1 ?>
0.0004  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 ?>
0.0002  
SET SESSION group_concat_max_len = 12288 ?>
0.0021  
SELECT `MV`.`title_id`, `MV`.`movie_id`, COUNT(DISTINCT MV.title_id) AS mv_count, `title`, `prefix`, `year`, `imdb_link`, `MT`.`imdb_id`, `MT`.`tmdb_id`, `overview`, `certification`, `runtime`, `genre_id_01`, `genre_id_02`, `genre_id_03`, MAX(MP.filename) AS filename, `G1`.`genre_name` AS `genre_name_01`, `G2`.`genre_name` AS `genre_name_02`, `G3`.`genre_name` AS `genre_name_03`, `date_viewed`, `notes`, `MV`.`format_id`, `FMT`.`format_name`, `MV`.`source_id`, `SRC`.`source_name`, `MV`.`device_id`, `DVC`.`device_name`, `MV`.`rating_id`, `STR`.`star_rating`, `rewatch`, GROUP_CONCAT(DISTINCT(DR.director_name) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS directors, GROUP_CONCAT(DISTINCT(DR.tmdb_director_id) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS director_ids, GROUP_CONCAT(DISTINCT(ACT.actor_name) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actors, GROUP_CONCAT(DISTINCT(ACT.tmdb_actor_id) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actor_ids
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movies` `MV` ON `MV`.`title_id` = `MT`.`title_id`
LEFT JOIN `ml_movie_posters` `MP` ON `MV`.`title_id` = `MP`.`title_id`
LEFT JOIN `ml_lookup_genres` `G1` ON `MV`.`genre_id_01` = `G1`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G2` ON `MV`.`genre_id_02` = `G2`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G3` ON `MV`.`genre_id_03` = `G3`.`genre_id`
LEFT JOIN `ml_lookup_formats` `FMT` ON `MV`.`format_id` = `FMT`.`format_id`
LEFT JOIN `ml_lookup_sources` `SRC` ON `MV`.`source_id` = `SRC`.`source_id`
LEFT JOIN `ml_lookup_devices` `DVC` ON `MV`.`device_id` = `DVC`.`device_id`
LEFT JOIN `ml_movie_ratings_ten_star` `STR` ON `MV`.`rating_id` = `STR`.`rating_id`
LEFT JOIN `ml_junction_movies_directors` `JMD` ON `MT`.`title_id` = `JMD`.`title_id`
LEFT JOIN `ml_directors_new` `DR` ON `JMD`.`tmdb_director_id` = `DR`.`tmdb_director_id`
LEFT JOIN `ml_junction_movies_actors` `JMA` ON `MT`.`title_id` = `JMA`.`title_id`
LEFT JOIN `ml_actors_new` `ACT` ON `JMA`.`tmdb_actor_id` = `ACT`.`tmdb_actor_id`
WHERE `MV`.`movie_id` = 7536
AND `MV`.`user_id` = 1
ORDER BY `date_viewed` DESC ?>
0.0002  
SET SESSION group_concat_max_len = 1024 ?>
0.0003  
SELECT `event_title`, `JME`.`event_id`
FROM `ml_junction_movies_events` `JME`
LEFT JOIN `ml_movie_events` `EV` ON `JME`.`event_id` = `EV`.`event_id`
WHERE `JME`.`movie_id` = 7536 ?>
0.0003  
SELECT `tag`, `JMT`.`tag_id`
FROM `ml_junction_movies_tags` `JMT`
LEFT JOIN `ml_tags` `MT` ON `JMT`.`tag_id` = `MT`.`tag_id`
WHERE `JMT`.`movie_id` = 7536 ?>
0.0002  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 ?>
0.0002  
SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7536
 LIMIT 1 ?>
0.0002  
SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '20'
 LIMIT 1 ?>
0.0004  
SELECT `MV2`.`date_viewed`, `MV2`.`movie_id`
FROM `ml_movies` `MV`
LEFT JOIN `ml_movies` `MV2` ON `MV`.`title_id` = `MV2`.`title_id` AND `MV`.`user_id` = `MV2`.`user_id`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7536
GROUP BY `MV2`.`movie_id`
ORDER BY `MV2`.`date_viewed` DESC ?>
0.0003  
SELECT `comment_id`, `comment`, `commenter_id`, `timestamp`, `username`, `email_address`
FROM `ml_comments` `MC`
JOIN `ml_users` `MU` ON `MU`.`user_id` = `MC`.`commenter_id`
WHERE `movie_id` = 7536 ?>
0.0004  
SELECT `username`, `date_viewed`, `MV`.`movie_id`
FROM `ml_users` `MU`
JOIN `ml_movies` `MV` ON `MV`.`user_id` = `MU`.`user_id`
JOIN `ml_movie_titles` `MT` ON `MT`.`title_id` = `MV`.`title_id`
WHERE `MT`.`title_id` = 4362
ORDER BY `date_viewed` DESC
 LIMIT 10 ?>
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)